org.ejml.alg.block.decomposition.qr

Class BlockHouseHolder

java.lang.Object

org.ejml.alg.block.decomposition.qr.BlockHouseHolder

public class BlockHouseHolder
extends java.lang.Object

Contains various helper functions for performing a block matrix QR decomposition.

Assumptions:

All submatrices are aligned along the inner blocks of the BlockMatrix64F. Some times vectors are assumed to have leading zeros and a one.

Constructor Summary

Constructors

Constructor and Description
BlockHouseHolder()

Method Summary

Methods

Modifier and Type	Method and Description
static void	add_row(int blockLength, D1Submatrix64F A, int rowA, double alpha, D1Submatrix64F B, int rowB, double beta, D1Submatrix64F C, int rowC, int zeroOffset, int end)
static boolean	computeHouseHolderCol(int blockLength, D1Submatrix64F Y, double[] gamma, int i) Computes the householder vector that is used to create reflector for the column.
static boolean	computeHouseHolderRow(int blockLength, D1Submatrix64F Y, double[] gamma, int i) Computes the householder vector from the specified row
static double	computeTauAndDivideCol(int blockLength, D1Submatrix64F Y, int col, double max) From the specified column of Y tau is computed and each element is divided by 'max'.
static double	computeTauAndDivideRow(int blockLength, D1Submatrix64F Y, int row, int colStart, double max) From the specified row of Y tau is computed and each element is divided by 'max'.
static void	computeW_Column(int blockLength, D1Submatrix64F Y, D1Submatrix64F W, double[] temp, double[] beta, int betaIndex) Computes W from the householder reflectors stored in the columns of the column block submatrix Y.
static void	computeY_t_V(int blockLength, D1Submatrix64F Y, int col, double[] temp) Computes YTv(j).
static void	computeZ(int blockLength, D1Submatrix64F Y, D1Submatrix64F W, int col, double[] temp, double beta) Computes the vector z and inserts it into 'W': z = - βj*(Vj + W*h) where h is a vector of length 'col' and was computed using computeY_t_V(int, org.ejml.data.D1Submatrix64F, int, double[]).
static boolean	decomposeQR_block_col(int blockLength, D1Submatrix64F Y, double[] gamma) Performs a standard QR decomposition on the specified submatrix that is one block wide.
static void	divideElementsCol(int blockLength, D1Submatrix64F Y, int col, double val) Divides the elements at the specified column by 'val'.
static double	findMaxCol(int blockLength, D1Submatrix64F Y, int col) Finds the element in the column with the largest absolute value.
static double	findMaxRow(int blockLength, D1Submatrix64F Y, int row, int colStart) Finds the element in the column with the largest absolute value.
static void	initializeW(int blockLength, D1Submatrix64F W, D1Submatrix64F Y, int widthB, double b) Sets W to its initial value using the first column of 'y' and the value of 'b': W = -βv where v = Y(:,0).
static double	innerProdCol(int blockLength, D1Submatrix64F A, int colA, int widthA, int colB, int widthB) Computes the inner product of column vector 'colA' against column vector 'colB' while taking account leading zeros and one. ret = aT*b
static double	innerProdRow(int blockLength, D1Submatrix64F A, int rowA, D1Submatrix64F B, int rowB, int zeroOffset) Computes the inner product of row vector 'rowA' against row vector 'rowB' while taking account leading zeros and one. ret = aT*b
static void	multAdd_zeros(int blockLength, D1Submatrix64F Y, D1Submatrix64F B, D1Submatrix64F C) Special multiplication that takes in account the zeros and one in Y, which is the matrix that stores the householder vectors.
static void	multBlockAdd_zerosone(double[] dataA, double[] dataB, double[] dataC, int indexA, int indexB, int indexC, int heightA, int widthA, int widthC) Inner block mult add operation that takes in account the zeros and on in dataA, which is the top part of the Y block vector that has the householder vectors. C = C + A * B
static void	multTransA_vecCol(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication on the block aligned submatrices.
protected static void	multTransABlockSet_lowerTriag(double[] dataA, double[] dataB, double[] dataC, int indexA, int indexB, int indexC, int heightA, int widthA, int widthC) Performs a matrix multiplication on an single inner block where A is assumed to be lower triangular with diagonal elements equal to 1. C = A^T * B
static void	rank1UpdateMultL_LeftCol(int blockLength, D1Submatrix64F A, int row, double gamma, int zeroOffset) Applies a householder reflector stored in row 'row' to the left column block.
static void	rank1UpdateMultL_Row(int blockLength, D1Submatrix64F A, int row, int colStart, double gamma) Applies a householder reflector stored in row 'row' to the remainder of the row in the block after it.
static void	rank1UpdateMultR_Col(int blockLength, D1Submatrix64F A, int col, double gamma) Applies a householder reflector stored in column 'col' to the remainder of the columns in the block after it.
static void	rank1UpdateMultR_TopRow(int blockLength, D1Submatrix64F A, int col, double gamma) Applies a householder reflector stored in column 'col' to the top block row (excluding the first column) of A.
static void	scale_row(int blockLength, D1Submatrix64F Y, D1Submatrix64F W, int row, int zeroOffset, double val) Scales the elements in the specified row starting at element colStart by 'val'. W = val*Y Takes in account zeros and leading one automatically.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BlockHouseHolder

public BlockHouseHolder()

Method Detail

decomposeQR_block_col

public static boolean decomposeQR_block_col(int blockLength,
                            D1Submatrix64F Y,
                            double[] gamma)

Performs a standard QR decomposition on the specified submatrix that is one block wide.

Parameters:

blockLength -

Y -

gamma -

computeHouseHolderCol

public static boolean computeHouseHolderCol(int blockLength,
                            D1Submatrix64F Y,
                            double[] gamma,
                            int i)

Computes the householder vector that is used to create reflector for the column. The results are stored in the original matrix.

The householder vector 'u' is computed as follows:

u(1) = 1
u(i) = x(i)/(τ + x(1))

The first element is implicitly assumed to be one and not written.

Returns:

If there was any problems or not. true = no problem.

computeHouseHolderRow

public static boolean computeHouseHolderRow(int blockLength,
                            D1Submatrix64F Y,
                            double[] gamma,
                            int i)

Computes the householder vector from the specified row

The householder vector 'u' is computed as follows:

u(1) = 1
u(i) = x(i)/(τ + x(1))

The first element is implicitly assumed to be one and not written.

Returns:

If there was any problems or not. true = no problem.

rank1UpdateMultR_Col

public static void rank1UpdateMultR_Col(int blockLength,
                        D1Submatrix64F A,
                        int col,
                        double gamma)

Applies a householder reflector stored in column 'col' to the remainder of the columns in the block after it. Takes in account leading zeros and one.

A = (I - γ*u*u^T)*A

Parameters:

A - submatrix that is at most one block wide and aligned along inner blocks

col - The column in A containing 'u'

rank1UpdateMultR_TopRow

public static void rank1UpdateMultR_TopRow(int blockLength,
                           D1Submatrix64F A,
                           int col,
                           double gamma)

Applies a householder reflector stored in column 'col' to the top block row (excluding the first column) of A. Takes in account leading zeros and one.

A = (I - γ*u*u^T)*A

Parameters:

A - submatrix that is at most one block wide and aligned along inner blocks

col - The column in A containing 'u'

rank1UpdateMultL_Row

public static void rank1UpdateMultL_Row(int blockLength,
                        D1Submatrix64F A,
                        int row,
                        int colStart,
                        double gamma)

Applies a householder reflector stored in row 'row' to the remainder of the row in the block after it. Takes in account leading zeros and one.

A = A*(I - γ*u*u^T)

Parameters:

A - submatrix that is block aligned

row - The row in A containing 'u'

colStart - First index in 'u' that the reflector starts at

rank1UpdateMultL_LeftCol

public static void rank1UpdateMultL_LeftCol(int blockLength,
                            D1Submatrix64F A,
                            int row,
                            double gamma,
                            int zeroOffset)

Applies a householder reflector stored in row 'row' to the left column block. Takes in account leading zeros and one.

A = A*(I - γ*u*u^T)

Parameters:

A - submatrix that is block aligned

row - The row in A containing 'u'

zeroOffset - How far off the diagonal is the first element in 'u'

innerProdCol

public static double innerProdCol(int blockLength,
                  D1Submatrix64F A,
                  int colA,
                  int widthA,
                  int colB,
                  int widthB)

Computes the inner product of column vector 'colA' against column vector 'colB' while taking account leading zeros and one.

ret = a^T*b

Column A is assumed to be a householder vector. Element at 'colA' is one and previous ones are zero.

Parameters:

blockLength -

A - block aligned submatrix.

colA - Column inside the block of first column vector.

widthA - how wide the column block that colA is inside of.

colB - Column inside the block of second column vector.

widthB - how wide the column block that colB is inside of.

Returns:

dot product of the two vectors.

innerProdRow

public static double innerProdRow(int blockLength,
                  D1Submatrix64F A,
                  int rowA,
                  D1Submatrix64F B,
                  int rowB,
                  int zeroOffset)

Computes the inner product of row vector 'rowA' against row vector 'rowB' while taking account leading zeros and one.

ret = a^T*b

Row A is assumed to be a householder vector. Element at 'colStartA' is one and previous elements are zero.

Parameters:

blockLength -

A - block aligned submatrix.

rowA - Row index inside the sub-matrix of first row vector has zeros and ones..

rowB - Row index inside the sub-matrix of second row vector.

Returns:

dot product of the two vectors.

add_row

public static void add_row(int blockLength,
           D1Submatrix64F A,
           int rowA,
           double alpha,
           D1Submatrix64F B,
           int rowB,
           double beta,
           D1Submatrix64F C,
           int rowC,
           int zeroOffset,
           int end)

divideElementsCol

public static void divideElementsCol(int blockLength,
                     D1Submatrix64F Y,
                     int col,
                     double val)

Divides the elements at the specified column by 'val'. Takes in account leading zeros and one.

scale_row

public static void scale_row(int blockLength,
             D1Submatrix64F Y,
             D1Submatrix64F W,
             int row,
             int zeroOffset,
             double val)

Scales the elements in the specified row starting at element colStart by 'val'.
W = val*Y Takes in account zeros and leading one automatically.

Parameters:

zeroOffset - How far off the diagonal is the first element in the vector.

computeTauAndDivideCol

public static double computeTauAndDivideCol(int blockLength,
                            D1Submatrix64F Y,
                            int col,
                            double max)

From the specified column of Y tau is computed and each element is divided by 'max'. See code below:

 for i=col:Y.numRows
   Y[i][col] = u[i][col] / max
   tau = tau + u[i][col]*u[i][col]
 end
 tau = sqrt(tau)
 if( Y[col][col] < 0 )
    tau = -tau;
 

computeTauAndDivideRow

public static double computeTauAndDivideRow(int blockLength,
                            D1Submatrix64F Y,
                            int row,
                            int colStart,
                            double max)

From the specified row of Y tau is computed and each element is divided by 'max'. See code below:

 for j=row:Y.numCols
   Y[row][j] = u[row][j] / max
   tau = tau + u[row][j]*u[row][j]
 end
 tau = sqrt(tau)
 if( Y[row][row] < 0 )
    tau = -tau;
 

Parameters:

row - Which row in the block will be processed

colStart - The first column that computation of tau will start at

max - used to normalize and prevent buffer over flow

findMaxCol

public static double findMaxCol(int blockLength,
                D1Submatrix64F Y,
                int col)

Finds the element in the column with the largest absolute value. The offset from zero is automatically taken in account based on the column.

findMaxRow

public static double findMaxRow(int blockLength,
                D1Submatrix64F Y,
                int row,
                int colStart)

Finds the element in the column with the largest absolute value. The offset from zero is automatically taken in account based on the column.

computeW_Column

public static void computeW_Column(int blockLength,
                   D1Submatrix64F Y,
                   D1Submatrix64F W,
                   double[] temp,
                   double[] beta,
                   int betaIndex)

Computes W from the householder reflectors stored in the columns of the column block submatrix Y.

Y = v⁽¹⁾
W = -β₁v⁽¹⁾
for j=2:r
z = -β(I +WY^T)v^(j)
W = [W z]
Y = [Y v^(j)]
end

where v^(.) are the house holder vectors, and r is the block length. Note that Y already contains the householder vectors so it does not need to be modified.

Y and W are assumed to have the same number of rows and columns.

Parameters:

Y - Input matrix containing householder vectors. Not modified.

W - Resulting W matrix. Modified.

temp - Used internally. Must have W.numCols elements.

beta - Beta's for householder vectors.

betaIndex - Index of first relevant beta.

initializeW

public static void initializeW(int blockLength,
               D1Submatrix64F W,
               D1Submatrix64F Y,
               int widthB,
               double b)

Sets W to its initial value using the first column of 'y' and the value of 'b':
W = -βv

where v = Y(:,0).

Parameters:

blockLength - size of the inner block

W - Submatrix being initialized.

Y - Contains householder vector

widthB - How wide the W block matrix is.

b - beta

computeZ

public static void computeZ(int blockLength,
            D1Submatrix64F Y,
            D1Submatrix64F W,
            int col,
            double[] temp,
            double beta)

Computes the vector z and inserts it into 'W':

z = - β_j*(V^j + W*h)

where h is a vector of length 'col' and was computed using computeY_t_V(int, org.ejml.data.D1Submatrix64F, int, double[]). V is a column in the Y matrix. Z is a column in the W matrix. Both Z and V are column 'col'.

computeY_t_V

public static void computeY_t_V(int blockLength,
                D1Submatrix64F Y,
                int col,
                double[] temp)

Computes Y^Tv^(j). Where Y are the columns before 'col' and v is the column at 'col'. The zeros and ones are taken in account. The solution is a vector with 'col' elements. width of Y must be along the block of original matrix A

Parameters:

temp - Temporary storage of least length 'col'

multAdd_zeros

public static void multAdd_zeros(int blockLength,
                 D1Submatrix64F Y,
                 D1Submatrix64F B,
                 D1Submatrix64F C)

Special multiplication that takes in account the zeros and one in Y, which is the matrix that stores the householder vectors.

multBlockAdd_zerosone

public static void multBlockAdd_zerosone(double[] dataA,
                         double[] dataB,
                         double[] dataC,
                         int indexA,
                         int indexB,
                         int indexC,
                         int heightA,
                         int widthA,
                         int widthC)

Inner block mult add operation that takes in account the zeros and on in dataA, which is the top part of the Y block vector that has the householder vectors.

C = C + A * B

multTransA_vecCol

public static void multTransA_vecCol(int blockLength,
                     D1Submatrix64F A,
                     D1Submatrix64F B,
                     D1Submatrix64F C)

Performs a matrix multiplication on the block aligned submatrices. A is assumed to be block column vector that is lower triangular with diagonal elements set to 1.

C = A^T * B

multTransABlockSet_lowerTriag

protected static void multTransABlockSet_lowerTriag(double[] dataA,
                                 double[] dataB,
                                 double[] dataC,
                                 int indexA,
                                 int indexB,
                                 int indexC,
                                 int heightA,
                                 int widthA,
                                 int widthC)

Performs a matrix multiplication on an single inner block where A is assumed to be lower triangular with diagonal elements equal to 1.

C = A^T * B