Uses of Class
org.ejml.data.D1Submatrix64F

Packages that use D1Submatrix64F

Package	Description
org.ejml.alg.block
org.ejml.alg.block.decomposition.bidiagonal
org.ejml.alg.block.decomposition.chol
org.ejml.alg.block.decomposition.hessenberg
org.ejml.alg.block.decomposition.qr

Uses of D1Submatrix64F in org.ejml.alg.block

Methods in org.ejml.alg.block with parameters of type D1Submatrix64F

Modifier and Type	Method and Description
static void	BlockVectorOps.add_row(int blockLength, D1Submatrix64F A, int rowA, double alpha, D1Submatrix64F B, int rowB, double beta, D1Submatrix64F C, int rowC, int offset, int end) Row vector add: add: ci = α*ai + βBi where 'a', 'b', and 'c' are row vectors within the row block vectors of A, B, and C respectively.
static boolean	BlockMatrixOps.blockAligned(int blockLength, D1Submatrix64F A) Checks to see if the submatrix has its boundaries along inner blocks.
static void	BlockVectorOps.div_row(int blockLength, D1Submatrix64F A, int rowA, double alpha, D1Submatrix64F B, int rowB, int offset, int end) Row vector divide: div: bi = ai/α where 'a' and 'b' are row vectors within the row block vector A and B.
static double	BlockVectorOps.dot_row_col(int blockLength, D1Submatrix64F A, int rowA, D1Submatrix64F B, int colB, int offset, int end) vector dot/inner product from one row vector and one column vector: dot: c = sum ai*bi where 'a' is a row vector 'b' is a column vectors within the row block vector A and B, and 'c' is a scalar.
static double	BlockVectorOps.dot_row(int blockLength, D1Submatrix64F A, int rowA, D1Submatrix64F B, int rowB, int offset, int end) Row vector dot/inner product: dot: c = sum ai*bi where 'a' and 'b' are row vectors within the row block vector A and B, and 'c' is a scalar.
static void	BlockTriangularSolver.invert(int blockLength, boolean upper, D1Submatrix64F T, D1Submatrix64F T_inv, double[] temp) Inverts an upper or lower triangular block submatrix.
static void	BlockTriangularSolver.invert(int blockLength, boolean upper, D1Submatrix64F T, double[] temp) Inverts an upper or lower triangular block submatrix.
static void	BlockMultiplication.mult(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication on BlockMatrix64F submatrices. c = a * b
static void	BlockMultiplication.multMinus(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication on BlockMatrix64F submatrices. c = c - a * b
static void	BlockMultiplication.multMinusTransA(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C)
static void	BlockMultiplication.multPlus(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication on BlockMatrix64F submatrices. c = c + a * b
static void	BlockMultiplication.multPlusTransA(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C)
static void	BlockMultiplication.multTransA(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication with a transpose on BlockMatrix64F submatrices. c = aT * b
static void	BlockMultiplication.multTransB(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication with a transpose on BlockMatrix64F submatrices. c = a * b T
static void	BlockInnerRankUpdate.rankNUpdate(int blockLength, double alpha, D1Submatrix64F A, D1Submatrix64F B) Performs: A = A + α B TB
static void	BlockVectorOps.scale_row(int blockLength, D1Submatrix64F A, int rowA, double alpha, D1Submatrix64F B, int rowB, int offset, int end) Row vector scale: scale: bi = α*ai where 'a' and 'b' are row vectors within the row block vector A and B.
static void	BlockTriangularSolver.solve(int blockLength, boolean upper, D1Submatrix64F T, D1Submatrix64F B, boolean transT) Performs an in-place solve operation on the provided block aligned sub-matrices. B = T-1 B where T is a triangular matrix.
static void	BlockTriangularSolver.solveBlock(int blockLength, boolean upper, D1Submatrix64F T, D1Submatrix64F B, boolean transT, boolean transB) Performs an in-place solve operation where T is contained in a single block. B = T-1 B where T is a triangular matrix contained in an inner block.
static void	BlockTriangularSolver.solveL(int blockLength, D1Submatrix64F L, D1Submatrix64F B, boolean transL) Solves lower triangular systems: B = L-1 B
static void	BlockTriangularSolver.solveR(int blockLength, D1Submatrix64F R, D1Submatrix64F B, boolean transR) Solves upper triangular systems: B = R-1 B
static void	BlockInnerRankUpdate.symmRankNMinus_L(int blockLength, D1Submatrix64F A, D1Submatrix64F B) Rank N update function for a symmetric inner submatrix and only operates on the lower triangular portion of the submatrix. A = A - B*BT
static void	BlockInnerRankUpdate.symmRankNMinus_U(int blockLength, D1Submatrix64F A, D1Submatrix64F B) Rank N update function for a symmetric inner submatrix and only operates on the upper triangular portion of the submatrix. A = A - B TB

Uses of D1Submatrix64F in org.ejml.alg.block.decomposition.bidiagonal

Methods in org.ejml.alg.block.decomposition.bidiagonal with parameters of type D1Submatrix64F

Modifier and Type	Method and Description
static boolean	BidiagonalHelper.bidiagOuterBlocks(int blockLength, D1Submatrix64F A, double[] gammasU, double[] gammasV) Performs a standard bidiagonal decomposition just on the outer blocks of the provided matrix

Uses of D1Submatrix64F in org.ejml.alg.block.decomposition.chol

Methods in org.ejml.alg.block.decomposition.chol with parameters of type D1Submatrix64F

Modifier and Type	Method and Description
static boolean	InnerCholesky_B64.lower(D1Submatrix64F T)
static boolean	InnerCholesky_B64.upper(D1Submatrix64F T)

Uses of D1Submatrix64F in org.ejml.alg.block.decomposition.hessenberg

Methods in org.ejml.alg.block.decomposition.hessenberg with parameters of type D1Submatrix64F

Modifier and Type	Method and Description
static void	TridiagonalHelper_B64.applyReflectorsToRow(int blockLength, D1Submatrix64F A, D1Submatrix64F V, int row) Applies the reflectors that have been computed previously to the specified row.
static void	TridiagonalHelper_B64.computeRowOfV(int blockLength, D1Submatrix64F A, D1Submatrix64F V, int row, double gamma) Final computation for a single row of 'v': v = y -(1/2)γ(y^T*u)*u
static void	TridiagonalHelper_B64.computeV_blockVector(int blockLength, D1Submatrix64F A, double[] gammas, D1Submatrix64F V) Given an already computed tridiagonal decomposition, compute the V row block vector. y(:) = A*u v(i) = y - (1/2)*γ*(y^T*u)*u
static void	TridiagonalHelper_B64.computeW_row(int blockLength, D1Submatrix64F Y, D1Submatrix64F W, double[] beta, int betaIndex) Computes W from the householder reflectors stored in the columns of the row block submatrix Y.
static void	TridiagonalHelper_B64.computeY(int blockLength, D1Submatrix64F A, D1Submatrix64F V, int row, double gamma) Computes the 'y' vector and stores the result in 'v' y = -γ(A + U*V^T + V*U^T)u
static double	TridiagonalHelper_B64.innerProdRowSymm(int blockLength, D1Submatrix64F A, int rowA, D1Submatrix64F B, int rowB, int zeroOffset)
static void	TridiagonalHelper_B64.multA_u(int blockLength, D1Submatrix64F A, D1Submatrix64F V, int row) Multiples the appropriate submatrix of A by the specified reflector and stores the result ('y') in V. y = A*u
static void	TridiagonalDecompositionHouseholder_B64.multPlusTransA(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) C = C + A^T*B
static void	TridiagonalHelper_B64.tridiagUpperRow(int blockLength, D1Submatrix64F A, double[] gammas, D1Submatrix64F V) Performs a tridiagonal decomposition on the upper row only.

Uses of D1Submatrix64F in org.ejml.alg.block.decomposition.qr

Methods in org.ejml.alg.block.decomposition.qr with parameters of type D1Submatrix64F

Modifier and Type	Method and Description
static void	BlockHouseHolder.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	BlockHouseHolder.computeHouseHolderCol(int blockLength, D1Submatrix64F Y, double[] gamma, int i) Computes the householder vector that is used to create reflector for the column.
static boolean	BlockHouseHolder.computeHouseHolderRow(int blockLength, D1Submatrix64F Y, double[] gamma, int i) Computes the householder vector from the specified row
static double	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.computeY_t_V(int blockLength, D1Submatrix64F Y, int col, double[] temp) Computes YTv(j).
static void	BlockHouseHolder.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 BlockHouseHolder.computeY_t_V(int, org.ejml.data.D1Submatrix64F, int, double[]).
static boolean	BlockHouseHolder.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	BlockHouseHolder.divideElementsCol(int blockLength, D1Submatrix64F Y, int col, double val) Divides the elements at the specified column by 'val'.
static double	BlockHouseHolder.findMaxCol(int blockLength, D1Submatrix64F Y, int col) Finds the element in the column with the largest absolute value.
static double	BlockHouseHolder.findMaxRow(int blockLength, D1Submatrix64F Y, int row, int colStart) Finds the element in the column with the largest absolute value.
static void	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.multTransA_vecCol(int blockLength, D1Submatrix64F A, D1Submatrix64F B, D1Submatrix64F C) Performs a matrix multiplication on the block aligned submatrices.
static void	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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	BlockHouseHolder.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.
protected void	QRDecompositionHouseholder_B64.updateA(D1Submatrix64F A) A = (I + W YT)TA A = A + Y (WTA) where A is a submatrix of the input matrix.