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Packages that use Matrix | |
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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 |
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Classes in org.apache.mahout.math that implement Matrix | |
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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 | |
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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 | |
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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 | |
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AbstractMatrix.TransposeViewVector(Matrix m,
int offset)
|
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AbstractMatrix.TransposeViewVector(Matrix m,
int offset,
boolean rowToColumn)
|
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CholeskyDecomposition(Matrix a)
|
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CholeskyDecomposition(Matrix a,
boolean pivot)
|
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DiagonalMatrix(Matrix values)
|
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MatrixVectorView(Matrix matrix,
int row,
int column,
int rowStride,
int columnStride)
|
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MatrixVectorView(Matrix matrix,
int row,
int column,
int rowStride,
int columnStride,
boolean isDense)
|
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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)
|
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PivotedMatrix(Matrix base,
int[] pivot)
|
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PivotedMatrix(Matrix base,
int[] rowPivot,
int[] columnPivot)
|
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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 |
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Methods in org.apache.mahout.math.decomposer.hebbian that return Matrix | |
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Matrix |
TrainingState.getCurrentEigens()
|
Matrix |
TrainingState.getTrainingProjections()
|
Methods in org.apache.mahout.math.decomposer.hebbian with parameters of type Matrix | |
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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 |
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Fields in org.apache.mahout.math.decomposer.lanczos declared as Matrix | |
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protected Matrix |
LanczosState.diagonalMatrix
|
Methods in org.apache.mahout.math.decomposer.lanczos that return Matrix | |
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Matrix |
LanczosState.getDiagonalMatrix()
|
Uses of Matrix in org.apache.mahout.math.random |
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Constructors in org.apache.mahout.math.random with parameters of type Matrix | |
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MultiNormal(Matrix a,
Vector mean)
Constructs a sampler with non-trivial scale matrix and mean. |
Uses of Matrix in org.apache.mahout.math.solver |
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Methods in org.apache.mahout.math.solver that return Matrix | |
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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 | |
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Vector |
LSMR.solve(Matrix A,
Vector b)
|
Constructors in org.apache.mahout.math.solver with parameters of type Matrix | |
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EigenDecomposition(Matrix x)
|
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EigenDecomposition(Matrix x,
boolean isSymmetric)
|
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JacobiConditioner(Matrix a)
|
Uses of Matrix in org.apache.mahout.math.ssvd |
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Methods in org.apache.mahout.math.ssvd that return Matrix | |
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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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