Uses of Interface
no.uib.cipr.matrix.Vector

Packages that use Vector
no.uib.cipr.matrix Dense and structured sparse matrices, along with matrix factorisations and solvers. 
no.uib.cipr.matrix.distributed Message passing interface (MPI) for Java. 
no.uib.cipr.matrix.sparse Unstructured sparse matrices and vectors with iterative solvers and preconditioners. 
 

Uses of Vector in no.uib.cipr.matrix
 

Classes in no.uib.cipr.matrix that implement Vector
 class AbstractVector
          Partial implementation of Vector.
 class DenseVector
          Dense vector.
 

Methods in no.uib.cipr.matrix that return Vector
 Vector AbstractVector.add(double alpha, Vector y)
           
 Vector DenseVector.add(double alpha, Vector y)
           
 Vector Vector.add(double alpha, Vector y)
          x = alpha*y + x
 Vector AbstractVector.add(Vector y)
           
 Vector DenseVector.add(Vector y)
           
 Vector Vector.add(Vector y)
          x = y + x
 Vector AbstractVector.copy()
           
 Vector Vector.copy()
          Creates a deep copy of the vector
static Vector Matrices.getSubVector(Vector x, int[] index)
          Returns a view into the given vector.
 Vector AbstractMatrix.mult(double alpha, Vector x, Vector y)
           
 Vector Matrix.mult(double alpha, Vector x, Vector y)
          y = alpha*A*x
 Vector AbstractMatrix.mult(Vector x, Vector y)
           
 Vector Matrix.mult(Vector x, Vector y)
          y = A*x
 Vector AbstractMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector BandMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector DenseMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector Matrix.multAdd(double alpha, Vector x, Vector y)
          y = alpha*A*x + y
 Vector AbstractMatrix.multAdd(Vector x, Vector y)
           
 Vector Matrix.multAdd(Vector x, Vector y)
          y = A*x + y
static Vector Matrices.random(int size)
          Creates a random vector.
static Vector Matrices.random(Vector x)
          Populates a vector with random numbers drawn from a uniform distribution between 0 and 1
 Vector AbstractVector.scale(double alpha)
           
 Vector Vector.scale(double alpha)
          x=alpha*x
 Vector AbstractVector.set(double alpha, Vector y)
           
 Vector DenseVector.set(double alpha, Vector y)
           
 Vector Vector.set(double alpha, Vector y)
          x=alpha*y
 Vector AbstractVector.set(Vector y)
           
 Vector DenseVector.set(Vector y)
           
 Vector Vector.set(Vector y)
          x=y
 Vector AbstractMatrix.solve(Vector b, Vector x)
           
 Vector BandMatrix.solve(Vector b, Vector x)
           
 Vector DenseMatrix.solve(Vector b, Vector x)
           
 Vector Matrix.solve(Vector b, Vector x)
          x = A\b.
 Vector SymmTridiagMatrix.solve(Vector b, Vector x)
           
 Vector TridiagMatrix.solve(Vector b, Vector x)
           
static Vector Matrices.synchronizedVector(Vector x)
          Returns a synchronized vector which wraps the given vector.
 Vector AbstractMatrix.transMult(double alpha, Vector x, Vector y)
           
 Vector Matrix.transMult(double alpha, Vector x, Vector y)
          y = alpha*AT*x
 Vector AbstractMatrix.transMult(Vector x, Vector y)
           
 Vector Matrix.transMult(Vector x, Vector y)
          y = AT*x
 Vector AbstractMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector BandMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector DenseMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector Matrix.transMultAdd(double alpha, Vector x, Vector y)
          y = alpha*AT*x + y
 Vector AbstractMatrix.transMultAdd(Vector x, Vector y)
           
 Vector Matrix.transMultAdd(Vector x, Vector y)
          y = AT*x + y
 Vector AbstractMatrix.transSolve(Vector b, Vector x)
           
 Vector DenseMatrix.transSolve(Vector b, Vector x)
           
 Vector Matrix.transSolve(Vector b, Vector x)
          x = AT\b.
 Vector SymmTridiagMatrix.transSolve(Vector b, Vector x)
           
 Vector AbstractVector.zero()
           
 Vector Vector.zero()
          Zeros all the entries in the vector, while preserving any underlying structure
 

Methods in no.uib.cipr.matrix with parameters of type Vector
 Vector AbstractVector.add(double alpha, Vector y)
           
 Vector DenseVector.add(double alpha, Vector y)
           
 Vector Vector.add(double alpha, Vector y)
          x = alpha*y + x
 Vector AbstractVector.add(Vector y)
           
 Vector DenseVector.add(Vector y)
           
 Vector Vector.add(Vector y)
          x = y + x
 void GivensRotation.apply(Vector x, int i1, int i2)
          Applies the Givens rotation to two elements of a vector
static int Matrices.cardinality(Vector x)
          Returns the number of non-zero entries in the given vector
protected  void AbstractMatrix.checkMultAdd(Vector x, Vector y)
          Checks the arguments to mult and multAdd
protected  void AbstractMatrix.checkRank1(Vector x, Vector y)
          Checks that a vector rank1 update is possible for the given vectors
protected  void AbstractMatrix.checkRank2(Vector x, Vector y)
          Checks that a vector rank2 update is legal with the given vectors
protected  void AbstractVector.checkSize(Vector y)
          Checks for conformant sizes
protected  void AbstractMatrix.checkSolve(Vector b, Vector x)
          Checks that a matrix inversion is legal for the given arguments.
protected  void AbstractMatrix.checkTransMultAdd(Vector x, Vector y)
          Checks the arguments to transMult and transMultAdd
 double AbstractVector.dot(Vector y)
           
 double DenseVector.dot(Vector y)
           
 double Vector.dot(Vector y)
          xT*y
static double[] Matrices.getArray(Vector x)
          Returns a dense array containing a copy of the given vector
static Vector Matrices.getSubVector(Vector x, int[] index)
          Returns a view into the given vector.
 Vector AbstractMatrix.mult(double alpha, Vector x, Vector y)
           
 Vector Matrix.mult(double alpha, Vector x, Vector y)
          y = alpha*A*x
 Vector AbstractMatrix.mult(Vector x, Vector y)
           
 Vector Matrix.mult(Vector x, Vector y)
          y = A*x
 Vector AbstractMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector BandMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector DenseMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector Matrix.multAdd(double alpha, Vector x, Vector y)
          y = alpha*A*x + y
 Vector AbstractMatrix.multAdd(Vector x, Vector y)
           
 Vector Matrix.multAdd(Vector x, Vector y)
          y = A*x + y
static Vector Matrices.random(Vector x)
          Populates a vector with random numbers drawn from a uniform distribution between 0 and 1
 Matrix AbstractMatrix.rank1(double alpha, Vector x)
           
 Matrix Matrix.rank1(double alpha, Vector x)
          A = alpha*x*xT + A.
 Matrix AbstractMatrix.rank1(double alpha, Vector x, Vector y)
           
 Matrix DenseMatrix.rank1(double alpha, Vector x, Vector y)
           
 Matrix Matrix.rank1(double alpha, Vector x, Vector y)
          A = alpha*x*yT + A.
 Matrix AbstractMatrix.rank1(Vector x)
           
 Matrix Matrix.rank1(Vector x)
          A = x*xT + A.
 Matrix AbstractMatrix.rank1(Vector x, Vector y)
           
 Matrix Matrix.rank1(Vector x, Vector y)
          A = x*yT + A.
 Matrix AbstractMatrix.rank2(double alpha, Vector x, Vector y)
           
 Matrix Matrix.rank2(double alpha, Vector x, Vector y)
          A = alpha*x*yT + alpha*y*xT + A.
 Matrix AbstractMatrix.rank2(Vector x, Vector y)
           
 Matrix Matrix.rank2(Vector x, Vector y)
          A = x*yT + y*xT + A.
 Vector AbstractVector.set(double alpha, Vector y)
           
 Vector DenseVector.set(double alpha, Vector y)
           
 Vector Vector.set(double alpha, Vector y)
          x=alpha*y
 Vector AbstractVector.set(Vector y)
           
 Vector DenseVector.set(Vector y)
           
 Vector Vector.set(Vector y)
          x=y
 Vector AbstractMatrix.solve(Vector b, Vector x)
           
 Vector BandMatrix.solve(Vector b, Vector x)
           
 Vector DenseMatrix.solve(Vector b, Vector x)
           
 Vector Matrix.solve(Vector b, Vector x)
          x = A\b.
 Vector SymmTridiagMatrix.solve(Vector b, Vector x)
           
 Vector TridiagMatrix.solve(Vector b, Vector x)
           
static Vector Matrices.synchronizedVector(Vector x)
          Returns a synchronized vector which wraps the given vector.
 Vector AbstractMatrix.transMult(double alpha, Vector x, Vector y)
           
 Vector Matrix.transMult(double alpha, Vector x, Vector y)
          y = alpha*AT*x
 Vector AbstractMatrix.transMult(Vector x, Vector y)
           
 Vector Matrix.transMult(Vector x, Vector y)
          y = AT*x
 Vector AbstractMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector BandMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector DenseMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector Matrix.transMultAdd(double alpha, Vector x, Vector y)
          y = alpha*AT*x + y
 Vector AbstractMatrix.transMultAdd(Vector x, Vector y)
           
 Vector Matrix.transMultAdd(Vector x, Vector y)
          y = AT*x + y
 Vector AbstractMatrix.transSolve(Vector b, Vector x)
           
 Vector DenseMatrix.transSolve(Vector b, Vector x)
           
 Vector Matrix.transSolve(Vector b, Vector x)
          x = AT\b.
 Vector SymmTridiagMatrix.transSolve(Vector b, Vector x)
           
 

Constructors in no.uib.cipr.matrix with parameters of type Vector
AbstractVector(Vector x)
          Constructor for AbstractVector, same size as x
DenseMatrix(Vector x)
          Constructor for DenseMatrix.
DenseMatrix(Vector[] x)
          Constructor for DenseMatrix.
DenseMatrix(Vector x, boolean deep)
          Constructor for DenseMatrix.
DenseVector(Vector x)
          Constructor for DenseVector
DenseVector(Vector x, boolean deep)
          Constructor for DenseVector
 

Uses of Vector in no.uib.cipr.matrix.distributed
 

Classes in no.uib.cipr.matrix.distributed that implement Vector
 class DistVector
          Deprecated. the no.uib.cipr.matrix.distributed package has been deprecated because of a number of hard to fix concurrency bugs. It is distributed only for backwards compatibility, but is not recommended. The utility of this package is questionable, as it does not allow distribution of computation between JVMs or across a network. For many people, distributed computing of multiple matrices can be achieved at a user-level through the JPPF Framework. Users who need to deal with few very large matrices may wish to implement their own storage classes and solvers using JPPF, but this will not be supported directly in matrix-toolkits-java.
 

Methods in no.uib.cipr.matrix.distributed that return Vector
 Vector BlockDiagonalPreconditioner.apply(Vector b, Vector x)
          Deprecated.  
 Vector TwoLevelPreconditioner.apply(Vector b, Vector x)
          Deprecated.  
 Vector DistVector.getLocal()
          Deprecated. Returns the local part of the vector
 Vector DistColMatrix.multAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 Vector DistRowMatrix.multAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 Vector BlockDiagonalPreconditioner.transApply(Vector b, Vector x)
          Deprecated.  
 Vector TwoLevelPreconditioner.transApply(Vector b, Vector x)
          Deprecated.  
 Vector DistColMatrix.transMultAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 Vector DistRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 

Methods in no.uib.cipr.matrix.distributed with parameters of type Vector
 DistVector DistVector.add(double alpha, Vector y)
          Deprecated.  
 Vector BlockDiagonalPreconditioner.apply(Vector b, Vector x)
          Deprecated.  
 Vector TwoLevelPreconditioner.apply(Vector b, Vector x)
          Deprecated.  
 double DistVector.dot(Vector y)
          Deprecated.  
 Vector DistColMatrix.multAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 Vector DistRowMatrix.multAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 DistVector DistVector.set(double alpha, Vector y)
          Deprecated.  
 Vector BlockDiagonalPreconditioner.transApply(Vector b, Vector x)
          Deprecated.  
 Vector TwoLevelPreconditioner.transApply(Vector b, Vector x)
          Deprecated.  
 Vector DistColMatrix.transMultAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 Vector DistRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
          Deprecated.  
 

Constructors in no.uib.cipr.matrix.distributed with parameters of type Vector
DistVector(int size, Communicator comm, Vector x)
          Deprecated. Constructor for DistVector
 

Uses of Vector in no.uib.cipr.matrix.sparse
 

Subinterfaces of Vector in no.uib.cipr.matrix.sparse
 interface ISparseVector
           
 

Classes in no.uib.cipr.matrix.sparse that implement Vector
 class SparseVector
          Sparse vector
 

Methods in no.uib.cipr.matrix.sparse that return Vector
 Vector AMG.apply(Vector b, Vector x)
           
 Vector DiagonalPreconditioner.apply(Vector b, Vector x)
           
 Vector ICC.apply(Vector b, Vector x)
           
 Vector ILU.apply(Vector b, Vector x)
           
 Vector ILUT.apply(Vector b, Vector x)
           
 Vector Preconditioner.apply(Vector b, Vector x)
          Solves the approximate problem with the given right hand side.
 Vector SSOR.apply(Vector b, Vector x)
           
 Vector CompDiagMatrix.mult(Vector x, Vector y)
           
 Vector CompRowMatrix.mult(Vector x, Vector y)
           
 Vector CompColMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector CompDiagMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector CompRowMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompColMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompRowMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector SparseVector.set(Vector y)
           
 Vector BiCG.solve(Matrix A, Vector b, Vector x)
           
 Vector BiCGstab.solve(Matrix A, Vector b, Vector x)
           
 Vector CG.solve(Matrix A, Vector b, Vector x)
           
 Vector CGS.solve(Matrix A, Vector b, Vector x)
           
 Vector Chebyshev.solve(Matrix A, Vector b, Vector x)
           
 Vector GMRES.solve(Matrix A, Vector b, Vector x)
           
 Vector IR.solve(Matrix A, Vector b, Vector x)
           
 Vector IterativeSolver.solve(Matrix A, Vector b, Vector x)
          Solves the given problem, writing result into the vector.
 Vector QMR.solve(Matrix A, Vector b, Vector x)
           
 Vector AMG.transApply(Vector b, Vector x)
           
 Vector DiagonalPreconditioner.transApply(Vector b, Vector x)
           
 Vector ICC.transApply(Vector b, Vector x)
           
 Vector ILU.transApply(Vector b, Vector x)
           
 Vector ILUT.transApply(Vector b, Vector x)
           
 Vector Preconditioner.transApply(Vector b, Vector x)
          Solves the approximate transpose problem with the given right hand side.
 Vector SSOR.transApply(Vector b, Vector x)
           
 Vector CompColMatrix.transMult(Vector x, Vector y)
           
 Vector CompRowMatrix.transMult(Vector x, Vector y)
           
 Vector CompColMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector CompDiagMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector CompRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompColMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 

Methods in no.uib.cipr.matrix.sparse with parameters of type Vector
 Vector AMG.apply(Vector b, Vector x)
           
 Vector DiagonalPreconditioner.apply(Vector b, Vector x)
           
 Vector ICC.apply(Vector b, Vector x)
           
 Vector ILU.apply(Vector b, Vector x)
           
 Vector ILUT.apply(Vector b, Vector x)
           
 Vector Preconditioner.apply(Vector b, Vector x)
          Solves the approximate problem with the given right hand side.
 Vector SSOR.apply(Vector b, Vector x)
           
protected  void AbstractIterativeSolver.checkSizes(Matrix A, Vector b, Vector x)
          Checks sizes of input data for IterativeSolver.solve(Matrix, Vector, Vector).
 boolean AbstractIterationMonitor.converged(double r, Vector x)
           
 boolean IterationMonitor.converged(double r, Vector x)
          Checks for convergence
 boolean AbstractIterationMonitor.converged(Vector r)
           
 boolean IterationMonitor.converged(Vector r)
          Checks for convergence
 boolean AbstractIterationMonitor.converged(Vector r, Vector x)
           
 boolean IterationMonitor.converged(Vector r, Vector x)
          Checks for convergence
protected abstract  boolean AbstractIterationMonitor.convergedI(double r, Vector x)
           
protected  boolean DefaultIterationMonitor.convergedI(double r, Vector x)
           
protected  boolean MatrixIterationMonitor.convergedI(double r, Vector x)
           
 double SparseVector.dot(Vector y)
           
 void IterationReporter.monitor(double r, Vector x, int i)
          Registers current information
 void NoIterationReporter.monitor(double r, Vector x, int i)
           
 void OutputIterationReporter.monitor(double r, Vector x, int i)
           
 Vector CompDiagMatrix.mult(Vector x, Vector y)
           
 Vector CompRowMatrix.mult(Vector x, Vector y)
           
 Vector CompColMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector CompDiagMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector CompRowMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompColMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompRowMatrix.multAdd(double alpha, Vector x, Vector y)
           
 Vector SparseVector.set(Vector y)
           
 Vector BiCG.solve(Matrix A, Vector b, Vector x)
           
 Vector BiCGstab.solve(Matrix A, Vector b, Vector x)
           
 Vector CG.solve(Matrix A, Vector b, Vector x)
           
 Vector CGS.solve(Matrix A, Vector b, Vector x)
           
 Vector Chebyshev.solve(Matrix A, Vector b, Vector x)
           
 Vector GMRES.solve(Matrix A, Vector b, Vector x)
           
 Vector IR.solve(Matrix A, Vector b, Vector x)
           
 Vector IterativeSolver.solve(Matrix A, Vector b, Vector x)
          Solves the given problem, writing result into the vector.
 Vector QMR.solve(Matrix A, Vector b, Vector x)
           
 Vector AMG.transApply(Vector b, Vector x)
           
 Vector DiagonalPreconditioner.transApply(Vector b, Vector x)
           
 Vector ICC.transApply(Vector b, Vector x)
           
 Vector ILU.transApply(Vector b, Vector x)
           
 Vector ILUT.transApply(Vector b, Vector x)
           
 Vector Preconditioner.transApply(Vector b, Vector x)
          Solves the approximate transpose problem with the given right hand side.
 Vector SSOR.transApply(Vector b, Vector x)
           
 Vector CompColMatrix.transMult(Vector x, Vector y)
           
 Vector CompRowMatrix.transMult(Vector x, Vector y)
           
 Vector CompColMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector CompDiagMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector CompRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompColMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 Vector FlexCompRowMatrix.transMultAdd(double alpha, Vector x, Vector y)
           
 

Constructors in no.uib.cipr.matrix.sparse with parameters of type Vector
BiCG(Vector template)
          Constructor for BiCG.
BiCGstab(Vector template)
          Constructor for BiCGstab.
CG(Vector template)
          Constructor for CG.
CGS(Vector template)
          Constructor for CGS.
Chebyshev(Vector template, double eigmin, double eigmax)
          Constructor for Chebyshev.
GMRES(Vector template)
          Constructor for GMRES.
GMRES(Vector template, int restart)
          Constructor for GMRES.
IR(Vector template)
          Constructor for IR.
QMR(Vector template)
          Constructor for QMR.
QMR(Vector template, Preconditioner M1, Preconditioner M2)
          Constructor for QMR.
SparseVector(Vector x)
          Constructor for SparseVector, and copies the contents from the supplied vector.
SparseVector(Vector x, boolean deep)
          Constructor for SparseVector, and copies the contents from the supplied vector.