Uses of Interface
org.apache.mahout.math.Matrix

Packages that use Matrix
org.apache.mahout.math Core base classes; Operations on primitive arrays such as sorting, partitioning and permuting. 
org.apache.mahout.math.decomposer.hebbian   
org.apache.mahout.math.decomposer.lanczos   
org.apache.mahout.math.random   
org.apache.mahout.math.solver   
org.apache.mahout.math.ssvd   
 

Uses of Matrix in org.apache.mahout.math
 

Classes in org.apache.mahout.math that implement Matrix
 class AbstractMatrix
          A few universal implementations of convenience functions
 class DenseMatrix
          Matrix of doubles implemented using a 2-d array
 class DenseSymmetricMatrix
          Economy packaging for a dense symmetric in-core matrix.
 class DiagonalMatrix
           
 class FileBasedMatrix
          Provides a way to get data from a file and treat it as if it were a matrix, but avoids putting all that data onto the Java heap.
 class FileBasedSparseBinaryMatrix
          Provides a way to get data from a file and treat it as if it were a matrix, but avoids putting all that data onto the Java heap.
 class MatrixView
          Implements subset view of a Matrix
 class PivotedMatrix
          Matrix that allows transparent row and column permutation.
 class RandomTrinaryMatrix
          Random matrix.
 class SparseColumnMatrix
          sparse matrix with general element values whose columns are accessible quickly.
 class SparseMatrix
          Doubly sparse matrix.
 class SparseRowMatrix
          sparse matrix with general element values whose rows are accessible quickly.
 class UpperTriangular
          Quick and dirty implementation of some Matrix methods over packed upper triangular matrix.
 

Methods in org.apache.mahout.math that return Matrix
 Matrix DenseMatrix.assign(DenseMatrix matrix)
           
 Matrix Matrix.assign(double value)
          Assign the value to all elements of the receiver
 Matrix DenseMatrix.assign(double value)
           
 Matrix AbstractMatrix.assign(double value)
           
 Matrix Matrix.assign(double[][] values)
          Assign the values to the receiver
 Matrix AbstractMatrix.assign(double[][] values)
           
 Matrix Matrix.assign(DoubleFunction function)
          Apply the function to each element of the receiver
 Matrix AbstractMatrix.assign(DoubleFunction function)
           
 Matrix Matrix.assign(Matrix other)
          Assign the other vector values to the receiver
 Matrix AbstractMatrix.assign(Matrix other)
           
 Matrix Matrix.assign(Matrix other, DoubleDoubleFunction function)
          Apply the function to each element of the receiver and the corresponding element of the other argument
 Matrix AbstractMatrix.assign(Matrix other, DoubleDoubleFunction function)
           
 Matrix UpperTriangular.assignColumn(int column, Vector other)
           
 Matrix SparseRowMatrix.assignColumn(int column, Vector other)
           
 Matrix SparseMatrix.assignColumn(int column, Vector other)
           
 Matrix SparseColumnMatrix.assignColumn(int column, Vector other)
           
 Matrix RandomTrinaryMatrix.assignColumn(int column, Vector other)
           
 Matrix PivotedMatrix.assignColumn(int column, Vector other)
          Assign the other vector values to the column of the receiver
 Matrix MatrixView.assignColumn(int column, Vector other)
           
 Matrix Matrix.assignColumn(int column, Vector other)
          Assign the other vector values to the column of the receiver
 Matrix FileBasedSparseBinaryMatrix.assignColumn(int column, Vector other)
          Assign the other vector values to the column of the receiver
 Matrix FileBasedMatrix.assignColumn(int column, Vector other)
          Assign the other vector values to the column of the receiver
 Matrix DiagonalMatrix.assignColumn(int column, Vector other)
           
 Matrix DenseMatrix.assignColumn(int column, Vector other)
           
 Matrix UpperTriangular.assignNonZeroElementsInRow(int row, double[] other)
           
 Matrix UpperTriangular.assignRow(int row, Vector other)
           
 Matrix SparseRowMatrix.assignRow(int row, Vector other)
           
 Matrix SparseMatrix.assignRow(int row, Vector other)
           
 Matrix SparseColumnMatrix.assignRow(int row, Vector other)
           
 Matrix RandomTrinaryMatrix.assignRow(int row, Vector other)
           
 Matrix PivotedMatrix.assignRow(int row, Vector other)
          Assign the other vector values to the row of the receiver
 Matrix MatrixView.assignRow(int row, Vector other)
           
 Matrix Matrix.assignRow(int row, Vector other)
          Assign the other vector values to the row of the receiver
 Matrix FileBasedSparseBinaryMatrix.assignRow(int row, Vector other)
          Assign the other vector values to the row of the receiver
 Matrix FileBasedMatrix.assignRow(int row, Vector other)
          Assign the other vector values to the row of the receiver
 Matrix DiagonalMatrix.assignRow(int row, Vector other)
          Assign the other vector values to the row of the receiver
 Matrix DenseMatrix.assignRow(int row, Vector other)
           
 Matrix SparseRowMatrix.clone()
           
 Matrix SparseMatrix.clone()
           
 Matrix SparseColumnMatrix.clone()
           
 Matrix PivotedMatrix.clone()
           
 Matrix MatrixView.clone()
           
 Matrix Matrix.clone()
          Return a copy of the recipient
 Matrix DenseMatrix.clone()
           
 Matrix AbstractMatrix.clone()
           
 Matrix Vector.cross(Vector other)
          Return the cross product of the receiver and the other vector
 Matrix NamedVector.cross(Vector other)
           
 Matrix DelegatingVector.cross(Vector other)
           
 Matrix AbstractVector.cross(Vector other)
           
 Matrix Matrix.divide(double x)
          Return a new matrix containing the values of the recipient divided by the argument
 Matrix AbstractMatrix.divide(double x)
           
static Matrix Matrices.functionalMatrixView(int rows, int columns, IntIntFunction gf)
          Shorter form of Matrices.functionalMatrixView(int, int, org.apache.mahout.math.function.IntIntFunction, boolean).
static Matrix Matrices.functionalMatrixView(int rows, int columns, IntIntFunction gf, boolean denseLike)
          Create a matrix view based on a function generator.
static Matrix Matrices.gaussianView(int rows, int columns, long seed)
          Random Gaussian matrix view.
 Matrix PivotedMatrix.getBase()
           
 Matrix CholeskyDecomposition.getL()
           
 Matrix QRDecomposition.getQ()
          Generates and returns the (economy-sized) orthogonal factor Q.
 Matrix QR.getQ()
           
 Matrix OldQRDecomposition.getQ()
          Generates and returns the (economy-sized) orthogonal factor Q.
 Matrix QRDecomposition.getR()
          Returns the upper triangular factor, R.
 Matrix QR.getR()
           
 Matrix OldQRDecomposition.getR()
          Returns the upper triangular factor, R.
 Matrix SingularValueDecomposition.getS()
           
 Matrix SingularValueDecomposition.getU()
          Returns the left singular vectors U.
 Matrix SingularValueDecomposition.getV()
          Returns the right singular vectors V.
 Matrix UpperTriangular.like()
           
 Matrix SparseRowMatrix.like()
           
 Matrix SparseMatrix.like()
           
 Matrix SparseColumnMatrix.like()
           
 Matrix RandomTrinaryMatrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix PivotedMatrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix MatrixView.like()
           
 Matrix Matrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix FileBasedSparseBinaryMatrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix FileBasedMatrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix DiagonalMatrix.like()
          Return an empty matrix of the same underlying class as the receiver
 Matrix DenseMatrix.like()
           
 Matrix UpperTriangular.like(int rows, int columns)
           
 Matrix SparseRowMatrix.like(int rows, int columns)
           
 Matrix SparseMatrix.like(int rows, int columns)
           
 Matrix SparseColumnMatrix.like(int rows, int columns)
           
 Matrix RandomTrinaryMatrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix PivotedMatrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix MatrixView.like(int rows, int columns)
           
 Matrix Matrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix FileBasedSparseBinaryMatrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix FileBasedMatrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix DiagonalMatrix.like(int rows, int columns)
          Returns an empty matrix of the same underlying class as the receiver and of the specified size.
 Matrix DenseMatrix.like(int rows, int columns)
           
protected  Matrix VectorView.matrixLike(int rows, int columns)
           
protected  Matrix SequentialAccessSparseVector.matrixLike(int rows, int columns)
           
protected  Matrix RandomAccessSparseVector.matrixLike(int rows, int columns)
           
protected  Matrix PermutedVectorView.matrixLike(int rows, int columns)
          Subclasses must override to return an appropriately sparse or dense result
protected  Matrix MatrixVectorView.matrixLike(int rows, int columns)
           
protected  Matrix DenseVector.matrixLike(int rows, int columns)
           
protected  Matrix ConstantVector.matrixLike(int rows, int columns)
          Subclasses must override to return an appropriately sparse or dense result
protected abstract  Matrix AbstractVector.matrixLike(int rows, int columns)
          Subclasses must override to return an appropriately sparse or dense result
protected  Matrix AbstractMatrix.TransposeViewVector.matrixLike(int rows, int columns)
           
 Matrix Matrix.minus(Matrix x)
          Return a new matrix containing the element by element difference of the recipient and the argument
 Matrix AbstractMatrix.minus(Matrix other)
           
 Matrix Matrix.plus(double x)
          Return a new matrix containing the sum of each value of the recipient and the argument
 Matrix AbstractMatrix.plus(double x)
           
 Matrix Matrix.plus(Matrix x)
          Return a new matrix containing the element by element sum of the recipient and the argument
 Matrix AbstractMatrix.plus(Matrix other)
           
 Matrix QRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B; returns X.
 Matrix QR.solve(Matrix B)
           
 Matrix OldQRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B; returns X.
 Matrix CholeskyDecomposition.solveLeft(Matrix z)
          Compute inv(L) * z efficiently.
 Matrix CholeskyDecomposition.solveRight(Matrix z)
          Compute z * inv(L') efficiently
static Matrix Matrices.symmetricUniformView(int rows, int columns, int seed)
          Matrix view based on uniform [-1,1) distribution.
 Matrix Matrix.times(double x)
          Return a new matrix containing the product of each value of the recipient and the argument
 Matrix AbstractMatrix.times(double x)
           
 Matrix Matrix.times(Matrix x)
          Return a new matrix containing the product of the recipient and the argument
 Matrix DiagonalMatrix.times(Matrix other)
           
 Matrix AbstractMatrix.times(Matrix other)
           
 Matrix MatrixTimesOps.timesLeft(Matrix that)
          Computes matrix product of (that * this)
 Matrix DiagonalMatrix.timesLeft(Matrix that)
           
 Matrix MatrixTimesOps.timesRight(Matrix that)
          computes matrix product of (this * that)
 Matrix DiagonalMatrix.timesRight(Matrix that)
           
 Matrix SparseRowMatrix.transpose()
           
 Matrix SparseColumnMatrix.transpose()
           
 Matrix Matrix.transpose()
          Return a new matrix that is the transpose of the receiver
 Matrix AbstractMatrix.transpose()
           
static Matrix Matrices.transposedView(Matrix m)
          A read-only transposed view of a matrix argument.
static Matrix Matrices.uniformView(int rows, int columns, int seed)
          Matrix view based on uniform [0,1) distribution.
 Matrix UpperTriangular.viewPart(int[] offset, int[] size)
           
 Matrix SparseRowMatrix.viewPart(int[] offset, int[] size)
           
 Matrix SparseMatrix.viewPart(int[] offset, int[] size)
           
 Matrix SparseColumnMatrix.viewPart(int[] offset, int[] size)
           
 Matrix RandomTrinaryMatrix.viewPart(int[] offset, int[] size)
          Return a new matrix containing the subset of the recipient
 Matrix PivotedMatrix.viewPart(int[] offset, int[] size)
          Return a new matrix containing the subset of the recipient
 Matrix MatrixView.viewPart(int[] offset, int[] size)
           
 Matrix Matrix.viewPart(int[] offset, int[] size)
          Return a view into part of a matrix.
 Matrix FileBasedSparseBinaryMatrix.viewPart(int[] offset, int[] size)
          Return a view into part of a matrix.
 Matrix FileBasedMatrix.viewPart(int[] offset, int[] size)
          Return a view into part of a matrix.
 Matrix DiagonalMatrix.viewPart(int[] offset, int[] size)
          Return a new matrix containing the subset of the recipient
 Matrix DenseMatrix.viewPart(int[] offset, int[] size)
           
 Matrix AbstractMatrix.viewPart(int[] offset, int[] size)
           
 Matrix Matrix.viewPart(int rowOffset, int rowsRequested, int columnOffset, int columnsRequested)
          Return a view into part of a matrix.
 Matrix DenseMatrix.viewPart(int rowOffset, int rowsRequested, int columnOffset, int columnsRequested)
           
 Matrix AbstractMatrix.viewPart(int rowOffset, int rowsRequested, int columnOffset, int columnsRequested)
           
 

Methods in org.apache.mahout.math with parameters of type Matrix
 Matrix Matrix.assign(Matrix other)
          Assign the other vector values to the receiver
 Matrix AbstractMatrix.assign(Matrix other)
           
 Matrix Matrix.assign(Matrix other, DoubleDoubleFunction function)
          Apply the function to each element of the receiver and the corresponding element of the other argument
 Matrix AbstractMatrix.assign(Matrix other, DoubleDoubleFunction function)
           
static double Algebra.getNorm(Matrix m)
          Compute Maximum Absolute Row Sum Norm of input Matrix m http://mathworld.wolfram.com/MaximumAbsoluteRowSumNorm.html
 Matrix Matrix.minus(Matrix x)
          Return a new matrix containing the element by element difference of the recipient and the argument
 Matrix AbstractMatrix.minus(Matrix other)
           
static Vector Algebra.mult(Matrix m, Vector v)
           
 Matrix Matrix.plus(Matrix x)
          Return a new matrix containing the element by element sum of the recipient and the argument
 Matrix AbstractMatrix.plus(Matrix other)
           
 Matrix QRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B; returns X.
 Matrix QR.solve(Matrix B)
           
 Matrix OldQRDecomposition.solve(Matrix B)
          Least squares solution of A*X = B; returns X.
 Matrix CholeskyDecomposition.solveLeft(Matrix z)
          Compute inv(L) * z efficiently.
 Matrix CholeskyDecomposition.solveRight(Matrix z)
          Compute z * inv(L') efficiently
 Matrix Matrix.times(Matrix x)
          Return a new matrix containing the product of the recipient and the argument
 Matrix DiagonalMatrix.times(Matrix other)
           
 Matrix AbstractMatrix.times(Matrix other)
           
 Matrix MatrixTimesOps.timesLeft(Matrix that)
          Computes matrix product of (that * this)
 Matrix DiagonalMatrix.timesLeft(Matrix that)
           
 Matrix MatrixTimesOps.timesRight(Matrix that)
          computes matrix product of (this * that)
 Matrix DiagonalMatrix.timesRight(Matrix that)
           
static Matrix Matrices.transposedView(Matrix m)
          A read-only transposed view of a matrix argument.
static void FileBasedSparseBinaryMatrix.writeMatrix(File f, Matrix m)
           
static void FileBasedMatrix.writeMatrix(File f, Matrix m)
           
 

Constructors in org.apache.mahout.math with parameters of type Matrix
AbstractMatrix.TransposeViewVector(Matrix m, int offset)
           
AbstractMatrix.TransposeViewVector(Matrix m, int offset, boolean rowToColumn)
           
CholeskyDecomposition(Matrix a)
           
CholeskyDecomposition(Matrix a, boolean pivot)
           
DiagonalMatrix(Matrix values)
           
MatrixVectorView(Matrix matrix, int row, int column, int rowStride, int columnStride)
           
MatrixVectorView(Matrix matrix, int row, int column, int rowStride, int columnStride, boolean isDense)
           
MatrixView(Matrix matrix, int[] offset, int[] size)
          Construct a view of the matrix with given offset and cardinality
OldQRDecomposition(Matrix a)
          Constructs and returns a new QR decomposition object; computed by Householder reflections; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
PivotedMatrix(Matrix base)
           
PivotedMatrix(Matrix base, int[] pivot)
           
PivotedMatrix(Matrix base, int[] rowPivot, int[] columnPivot)
           
QRDecomposition(Matrix a)
          Constructs and returns a new QR decomposition object; computed by Householder reflections; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
SingularValueDecomposition(Matrix arg)
          Constructs and returns a new singular value decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
 

Uses of Matrix in org.apache.mahout.math.decomposer.hebbian
 

Methods in org.apache.mahout.math.decomposer.hebbian that return Matrix
 Matrix TrainingState.getCurrentEigens()
           
 Matrix TrainingState.getTrainingProjections()
           
 

Methods in org.apache.mahout.math.decomposer.hebbian with parameters of type Matrix
protected  boolean HebbianSolver.hasNotConverged(Vector currentPseudoEigen, Matrix corpus, TrainingState state)
          Uses the SingularVectorVerifier to check for convergence
 void TrainingState.setCurrentEigens(Matrix currentEigens)
           
 void TrainingState.setTrainingProjections(Matrix trainingProjections)
           
 TrainingState HebbianSolver.solve(Matrix corpus, int desiredRank)
          Primary singular vector solving method.
protected  EigenStatus HebbianSolver.verify(Matrix corpus, Vector currentPseudoEigen)
           
 

Uses of Matrix in org.apache.mahout.math.decomposer.lanczos
 

Fields in org.apache.mahout.math.decomposer.lanczos declared as Matrix
protected  Matrix LanczosState.diagonalMatrix
           
 

Methods in org.apache.mahout.math.decomposer.lanczos that return Matrix
 Matrix LanczosState.getDiagonalMatrix()
           
 

Uses of Matrix in org.apache.mahout.math.random
 

Constructors in org.apache.mahout.math.random with parameters of type Matrix
MultiNormal(Matrix a, Vector mean)
          Constructs a sampler with non-trivial scale matrix and mean.
 

Uses of Matrix in org.apache.mahout.math.solver
 

Methods in org.apache.mahout.math.solver that return Matrix
 Matrix EigenDecomposition.getD()
          Return the block diagonal eigenvalue matrix
 Matrix EigenDecomposition.getV()
          Return the eigenvector matrix
 

Methods in org.apache.mahout.math.solver with parameters of type Matrix
 Vector LSMR.solve(Matrix A, Vector b)
           
 

Constructors in org.apache.mahout.math.solver with parameters of type Matrix
EigenDecomposition(Matrix x)
           
EigenDecomposition(Matrix x, boolean isSymmetric)
           
JacobiConditioner(Matrix a)
           
 

Uses of Matrix in org.apache.mahout.math.ssvd
 

Methods in org.apache.mahout.math.ssvd that return Matrix
 Matrix SequentialBigSvd.getU()
           
 Matrix SequentialBigSvd.getV()
           
 

Constructors in org.apache.mahout.math.ssvd with parameters of type Matrix
SequentialBigSvd(Matrix A, int p)
           
 



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