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| Uses of DenseMatrix64F in org.ejml |
|---|
| Methods in org.ejml that return DenseMatrix64F | |
|---|---|
static DenseMatrix64F |
UtilEjml.parseMatrix(String s,
int numColumns)
Give a string of numbers it returns a DenseMatrix |
| Uses of DenseMatrix64F in org.ejml.alg.block |
|---|
| Methods in org.ejml.alg.block that return DenseMatrix64F | |
|---|---|
static DenseMatrix64F |
BlockMatrixOps.convert(BlockMatrix64F src,
DenseMatrix64F dst)
Converts a row major block matrix into a row major matrix. |
| Methods in org.ejml.alg.block with parameters of type DenseMatrix64F | |
|---|---|
static DenseMatrix64F |
BlockMatrixOps.convert(BlockMatrix64F src,
DenseMatrix64F dst)
Converts a row major block matrix into a row major matrix. |
static BlockMatrix64F |
BlockMatrixOps.convert(DenseMatrix64F A)
|
static void |
BlockMatrixOps.convert(DenseMatrix64F src,
BlockMatrix64F dst)
Converts a row major matrix into a row major block matrix. |
static BlockMatrix64F |
BlockMatrixOps.convert(DenseMatrix64F A,
int blockLength)
|
static void |
BlockMatrixOps.convertTranSrc(DenseMatrix64F src,
BlockMatrix64F dst)
Converts the transpose of a row major matrix into a row major block matrix. |
| Uses of DenseMatrix64F in org.ejml.alg.block.decomposition.hessenberg |
|---|
| Fields in org.ejml.alg.block.decomposition.hessenberg declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
TridiagonalDecompositionBlockHouseholder.zerosM
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition |
|---|
| Methods in org.ejml.alg.dense.decomposition that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
QRPDecomposition.getPivotMatrix(DenseMatrix64F P)
|
| Methods in org.ejml.alg.dense.decomposition that return types with arguments of type DenseMatrix64F | |
|---|---|
static CholeskyDecomposition<DenseMatrix64F> |
DecompositionFactory.chol(int widthWidth,
boolean lower)
If you don't know which Cholesky algorithm to use, call this function to select what is most likely the best one for you. |
static EigenDecomposition<DenseMatrix64F> |
DecompositionFactory.eig(int matrixWidth)
Returns a new eigenvalue decomposition. |
static EigenDecomposition<DenseMatrix64F> |
DecompositionFactory.eig(int matrixWidth,
boolean needVectors)
Same as DecompositionFactory.eig(int) but can turn on and off computing eigen vectors |
static EigenDecomposition<DenseMatrix64F> |
DecompositionFactory.eigGeneral(int matrixSize,
boolean computeVectors)
Creates a new EigenDecomposition that will work with any matrix. |
static EigenDecomposition<DenseMatrix64F> |
DecompositionFactory.eigSymm(int matrixWidth,
boolean computeVectors)
Creates a new EigenDecomposition that will only work with symmetric matrices. |
static LUDecomposition<DenseMatrix64F> |
DecompositionFactory.lu(int matrixWidth)
Returns a new instance of the Lower Upper (LU) decomposition. |
static QRDecomposition<DenseMatrix64F> |
DecompositionFactory.qr(int numRows,
int numCols)
Returns a new instance of the QR decomposition. |
static QRPDecomposition<DenseMatrix64F> |
DecompositionFactory.qrp(int numRows,
int numCols)
Returns a new instance of QR decomposition with column pivoting. A*P = Q*R where A is the input matrix, and P is the pivot matrix. |
static SingularValueDecomposition<DenseMatrix64F> |
DecompositionFactory.svd(int numRows,
int numCols)
Returns a new instance of a SingularValueDecomposition which will compute the full decomposition.. |
static SingularValueDecomposition<DenseMatrix64F> |
DecompositionFactory.svd(int numRows,
int numCols,
boolean needU,
boolean needV,
boolean compact)
Returns a new instance of a SingularValueDecomposition which can be configured to compute U and V matrices or not, be in compact form. |
static TridiagonalSimilarDecomposition<DenseMatrix64F> |
DecompositionFactory.tridiagonal(int matrixWidth)
Checks to see if the passed in tridiagonal decomposition is of the appropriate type for the matrix of the provided size. |
| Methods in org.ejml.alg.dense.decomposition with parameters of type DenseMatrix64F | |
|---|---|
boolean |
BaseDecompositionBlock64.decompose(DenseMatrix64F A)
|
DenseMatrix64F |
QRPDecomposition.getPivotMatrix(DenseMatrix64F P)
|
static double |
DecompositionFactory.quality(DenseMatrix64F orig,
DenseMatrix64F U,
DenseMatrix64F W,
DenseMatrix64F Vt)
|
static double |
DecompositionFactory.quality(DenseMatrix64F orig,
EigenDecomposition<DenseMatrix64F> eig)
Computes a metric which measures the the quality of an eigen value decomposition. |
static double |
DecompositionFactory.quality(DenseMatrix64F orig,
SingularValueDecomposition<DenseMatrix64F> svd)
Computes a metric which measures the the quality of a singular value decomposition. |
| Method parameters in org.ejml.alg.dense.decomposition with type arguments of type DenseMatrix64F | |
|---|---|
static double |
DecompositionFactory.quality(DenseMatrix64F orig,
EigenDecomposition<DenseMatrix64F> eig)
Computes a metric which measures the the quality of an eigen value decomposition. |
static double |
DecompositionFactory.quality(DenseMatrix64F orig,
SingularValueDecomposition<DenseMatrix64F> svd)
Computes a metric which measures the the quality of a singular value decomposition. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.bidiagonal |
|---|
| Methods in org.ejml.alg.dense.decomposition.bidiagonal that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
BidiagonalDecompositionTall.getB(DenseMatrix64F B,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getB(DenseMatrix64F B,
boolean compact)
Returns the bidiagonal matrix. |
DenseMatrix64F |
BidiagonalDecompositionTall.getU(DenseMatrix64F U,
boolean transpose,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getU(DenseMatrix64F U,
boolean transpose,
boolean compact)
Returns the orthogonal U matrix. |
DenseMatrix64F |
BidiagonalDecompositionRow.getUBV()
The raw UBV matrix that is stored internally. |
DenseMatrix64F |
BidiagonalDecompositionTall.getV(DenseMatrix64F V,
boolean transpose,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getV(DenseMatrix64F V,
boolean transpose,
boolean compact)
Returns the orthogonal V matrix. |
static DenseMatrix64F |
BidiagonalDecompositionRow.handleB(DenseMatrix64F B,
boolean compact,
int m,
int n,
int min)
|
static DenseMatrix64F |
BidiagonalDecompositionRow.handleU(DenseMatrix64F U,
boolean transpose,
boolean compact,
int m,
int n,
int min)
|
static DenseMatrix64F |
BidiagonalDecompositionRow.handleV(DenseMatrix64F V,
boolean transpose,
boolean compact,
int m,
int n,
int min)
|
| Methods in org.ejml.alg.dense.decomposition.bidiagonal with parameters of type DenseMatrix64F | |
|---|---|
boolean |
BidiagonalDecompositionNaive.decompose(DenseMatrix64F A)
Computes the decomposition of the provided matrix. |
boolean |
BidiagonalDecompositionTall.decompose(DenseMatrix64F orig)
|
boolean |
BidiagonalDecompositionRow.decompose(DenseMatrix64F A)
Computes the decomposition of the provided matrix. |
DenseMatrix64F |
BidiagonalDecompositionTall.getB(DenseMatrix64F B,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getB(DenseMatrix64F B,
boolean compact)
Returns the bidiagonal matrix. |
DenseMatrix64F |
BidiagonalDecompositionTall.getU(DenseMatrix64F U,
boolean transpose,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getU(DenseMatrix64F U,
boolean transpose,
boolean compact)
Returns the orthogonal U matrix. |
DenseMatrix64F |
BidiagonalDecompositionTall.getV(DenseMatrix64F V,
boolean transpose,
boolean compact)
|
DenseMatrix64F |
BidiagonalDecompositionRow.getV(DenseMatrix64F V,
boolean transpose,
boolean compact)
Returns the orthogonal V matrix. |
static DenseMatrix64F |
BidiagonalDecompositionRow.handleB(DenseMatrix64F B,
boolean compact,
int m,
int n,
int min)
|
static DenseMatrix64F |
BidiagonalDecompositionRow.handleU(DenseMatrix64F U,
boolean transpose,
boolean compact,
int m,
int n,
int min)
|
static DenseMatrix64F |
BidiagonalDecompositionRow.handleV(DenseMatrix64F V,
boolean transpose,
boolean compact,
int m,
int n,
int min)
|
protected void |
BidiagonalDecompositionNaive.init(DenseMatrix64F A)
|
protected void |
BidiagonalDecompositionRow.init(DenseMatrix64F A)
Sets up internal data structures and creates a copy of the input matrix. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.chol |
|---|
| Fields in org.ejml.alg.dense.decomposition.chol declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
CholeskyDecompositionCommon.T
|
| Methods in org.ejml.alg.dense.decomposition.chol that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
CholeskyDecompositionLDL.getL()
Returns L matrix from the decomposition. L*D*LT=A |
DenseMatrix64F |
CholeskyDecompositionCommon.getT()
Returns the triangular matrix from the decomposition. |
DenseMatrix64F |
CholeskyDecompositionBlock64.getT(DenseMatrix64F T)
|
DenseMatrix64F |
CholeskyDecompositionCommon.getT(DenseMatrix64F T)
|
| Methods in org.ejml.alg.dense.decomposition.chol with parameters of type DenseMatrix64F | |
|---|---|
boolean |
CholeskyDecompositionCommon.decompose(DenseMatrix64F mat)
Performs Choleksy decomposition on the provided matrix. |
boolean |
CholeskyDecompositionLDL.decompose(DenseMatrix64F mat)
Performs Choleksy decomposition on the provided matrix. |
DenseMatrix64F |
CholeskyDecompositionBlock64.getT(DenseMatrix64F T)
|
DenseMatrix64F |
CholeskyDecompositionCommon.getT(DenseMatrix64F T)
|
static void |
CholeskyDecompositionBlock.solveL_special(double[] L,
DenseMatrix64F b_src,
int indexSrc,
int indexDst,
DenseMatrix64F B)
This is a variation on the TriangularSolver.solveL(double[], double[], int) function. |
static void |
CholeskyDecompositionBlock.symmRankTranA_sub(DenseMatrix64F a,
DenseMatrix64F c,
int startIndexC)
Performs this operation: c = c - aTa where c is a submatrix. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.eig |
|---|
| Methods in org.ejml.alg.dense.decomposition.eig that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
EigenPowerMethod.getEigenVector()
|
DenseMatrix64F |
SymmetricQRAlgorithmDecomposition.getEigenVector(int index)
|
DenseMatrix64F |
WatchedDoubleStepQRDecomposition.getEigenVector(int index)
|
DenseMatrix64F |
SwitchingEigenDecomposition.getEigenVector(int index)
|
| Methods in org.ejml.alg.dense.decomposition.eig with parameters of type DenseMatrix64F | |
|---|---|
boolean |
EigenPowerMethod.computeDirect(DenseMatrix64F A)
This method computes the eigen vector with the largest eigen value by using the direct power method. |
boolean |
EigenPowerMethod.computeShiftDirect(DenseMatrix64F A,
double alpha)
Computes the most dominant eigen vector of A using a shifted matrix. |
boolean |
EigenPowerMethod.computeShiftInvert(DenseMatrix64F A,
double alpha)
Computes the most dominant eigen vector of A using an inverted shifted matrix. |
boolean |
SymmetricQRAlgorithmDecomposition.decompose(DenseMatrix64F orig)
Decomposes the matrix using the QR algorithm. |
boolean |
WatchedDoubleStepQRDecomposition.decompose(DenseMatrix64F A)
|
boolean |
SwitchingEigenDecomposition.decompose(DenseMatrix64F orig)
|
boolean |
EigenvalueExtractor.process(DenseMatrix64F A)
|
void |
EigenPowerMethod.setSeed(DenseMatrix64F seed)
Sets the value of the vector to use in the start of the iterations. |
| Constructor parameters in org.ejml.alg.dense.decomposition.eig with type arguments of type DenseMatrix64F | |
|---|---|
SymmetricQRAlgorithmDecomposition(TridiagonalSimilarDecomposition<DenseMatrix64F> decomp,
boolean computeVectors)
|
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.eig.symm |
|---|
| Fields in org.ejml.alg.dense.decomposition.eig.symm declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
SymmetricQREigenHelper.Q
|
| Methods in org.ejml.alg.dense.decomposition.eig.symm that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
SymmetricQrAlgorithm.getQ()
|
| Methods in org.ejml.alg.dense.decomposition.eig.symm with parameters of type DenseMatrix64F | |
|---|---|
void |
SymmetricQrAlgorithm.setQ(DenseMatrix64F q)
|
void |
SymmetricQREigenHelper.setQ(DenseMatrix64F q)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.eig.watched |
|---|
| Fields in org.ejml.alg.dense.decomposition.eig.watched declared as DenseMatrix64F | |
|---|---|
DenseMatrix64F |
WatchedDoubleStepQREigen.Q
|
| Methods in org.ejml.alg.dense.decomposition.eig.watched that return DenseMatrix64F | |
|---|---|
DenseMatrix64F[] |
WatchedDoubleStepQREigenvector.getEigenvectors()
|
DenseMatrix64F |
WatchedDoubleStepQREigenvector.getQ()
|
| Methods in org.ejml.alg.dense.decomposition.eig.watched with parameters of type DenseMatrix64F | |
|---|---|
boolean |
WatchedDoubleStepQREigenvector.extractVectors(DenseMatrix64F Q_h)
|
boolean |
WatchedDoubleStepQREigenvalue.process(DenseMatrix64F origA)
|
boolean |
WatchedDoubleStepQREigenvector.process(WatchedDoubleStepQREigen implicit,
DenseMatrix64F A,
DenseMatrix64F Q_h)
|
void |
WatchedDoubleStepQREigen.setQ(DenseMatrix64F Q)
|
void |
WatchedDoubleStepQREigen.setup(DenseMatrix64F A)
|
void |
WatchedDoubleStepQREigenvalue.setup(DenseMatrix64F A)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.hessenberg |
|---|
| Methods in org.ejml.alg.dense.decomposition.hessenberg that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
HessenbergSimilarDecomposition.getH(DenseMatrix64F H)
An upper Hessenberg matrix from the decompostion. |
DenseMatrix64F |
HessenbergSimilarDecomposition.getQ(DenseMatrix64F Q)
An orthogonal matrix that has the following property: H = QTAQ |
DenseMatrix64F |
TridiagonalDecompositionHouseholderOrig.getQ(DenseMatrix64F Q)
An orthogonal matrix that has the following property: T = QTAQ |
DenseMatrix64F |
TridiagonalDecompositionBlock.getQ(DenseMatrix64F Q,
boolean transposed)
|
DenseMatrix64F |
TridiagonalDecompositionHouseholder.getQ(DenseMatrix64F Q,
boolean transposed)
An orthogonal matrix that has the following property: T = QTAQ |
DenseMatrix64F |
HessenbergSimilarDecomposition.getQH()
The raw QH matrix that is stored internally. |
DenseMatrix64F |
TridiagonalDecompositionHouseholder.getQT()
Returns the internal matrix where the decomposed results are stored. |
DenseMatrix64F |
TridiagonalDecompositionHouseholderOrig.getQT()
Returns the interal matrix where the decomposed results are stored. |
DenseMatrix64F |
TridiagonalDecompositionBlock.getT(DenseMatrix64F T)
|
DenseMatrix64F |
TridiagonalDecompositionHouseholder.getT(DenseMatrix64F T)
Extracts the tridiagonal matrix found in the decomposition. |
DenseMatrix64F |
TridiagonalDecompositionHouseholderOrig.getT(DenseMatrix64F T)
Extracts the tridiagonal matrix found in the decomposition. |
| Methods in org.ejml.alg.dense.decomposition.hessenberg with parameters of type DenseMatrix64F | |
|---|---|
boolean |
HessenbergSimilarDecomposition.decompose(DenseMatrix64F A)
Computes the decomposition of the provided matrix. |
boolean |
TridiagonalDecompositionHouseholder.decompose(DenseMatrix64F A)
Decomposes the provided symmetric matrix. |
void |
TridiagonalDecompositionHouseholderOrig.decompose(DenseMatrix64F A)
Decomposes the provided symmetric matrix. |
DenseMatrix64F |
HessenbergSimilarDecomposition.getH(DenseMatrix64F H)
An upper Hessenberg matrix from the decompostion. |
DenseMatrix64F |
HessenbergSimilarDecomposition.getQ(DenseMatrix64F Q)
An orthogonal matrix that has the following property: H = QTAQ |
DenseMatrix64F |
TridiagonalDecompositionHouseholderOrig.getQ(DenseMatrix64F Q)
An orthogonal matrix that has the following property: T = QTAQ |
DenseMatrix64F |
TridiagonalDecompositionBlock.getQ(DenseMatrix64F Q,
boolean transposed)
|
DenseMatrix64F |
TridiagonalDecompositionHouseholder.getQ(DenseMatrix64F Q,
boolean transposed)
An orthogonal matrix that has the following property: T = QTAQ |
DenseMatrix64F |
TridiagonalDecompositionBlock.getT(DenseMatrix64F T)
|
DenseMatrix64F |
TridiagonalDecompositionHouseholder.getT(DenseMatrix64F T)
Extracts the tridiagonal matrix found in the decomposition. |
DenseMatrix64F |
TridiagonalDecompositionHouseholderOrig.getT(DenseMatrix64F T)
Extracts the tridiagonal matrix found in the decomposition. |
void |
TridiagonalDecompositionHouseholder.init(DenseMatrix64F A)
If needed declares and sets up internal data structures. |
void |
TridiagonalDecompositionHouseholderOrig.init(DenseMatrix64F A)
If needed declares and sets up internal data structures. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.lu |
|---|
| Fields in org.ejml.alg.dense.decomposition.lu declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
LUDecompositionBase.LU
|
| Methods in org.ejml.alg.dense.decomposition.lu that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
LUDecompositionBase.getLower(DenseMatrix64F lower)
Writes the lower triangular matrix into the specified matrix. |
DenseMatrix64F |
LUDecompositionBase.getLU()
|
DenseMatrix64F |
LUDecompositionBase.getPivot(DenseMatrix64F pivot)
|
DenseMatrix64F |
LUDecompositionBase.getUpper(DenseMatrix64F upper)
Writes the upper triangular matrix into the specified matrix. |
| Methods in org.ejml.alg.dense.decomposition.lu with parameters of type DenseMatrix64F | |
|---|---|
boolean |
LUDecompositionNR.decompose(DenseMatrix64F orig)
This implementation of LU Decomposition uses the algorithm specified below: "Numerical Recipes The Art of Scientific Computing", Third Edition, Pages 48-55 |
boolean |
LUDecompositionAlt.decompose(DenseMatrix64F a)
This is a modified version of what was found in the JAMA package. |
protected void |
LUDecompositionBase.decomposeCommonInit(DenseMatrix64F a)
|
DenseMatrix64F |
LUDecompositionBase.getLower(DenseMatrix64F lower)
Writes the lower triangular matrix into the specified matrix. |
DenseMatrix64F |
LUDecompositionBase.getPivot(DenseMatrix64F pivot)
|
DenseMatrix64F |
LUDecompositionBase.getUpper(DenseMatrix64F upper)
Writes the upper triangular matrix into the specified matrix. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.qr |
|---|
| Fields in org.ejml.alg.dense.decomposition.qr declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
QRDecompositionHouseholderTran.QR
Where the Q and R matrices are stored. |
protected DenseMatrix64F |
QRDecompositionHouseholder.QR
Where the Q and R matrices are stored. |
| Methods in org.ejml.alg.dense.decomposition.qr that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
QRColPivDecompositionHouseholderColumn.getPivotMatrix(DenseMatrix64F P)
|
DenseMatrix64F |
QRDecompositionHouseholderColumn.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the imformation stored in the QR matrix. |
DenseMatrix64F |
QRColPivDecompositionHouseholderColumn.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the information stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionBlock64.getQ(DenseMatrix64F Q,
boolean compact)
|
DenseMatrix64F |
QRDecompositionHouseholderTran.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the information stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionHouseholder.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the imformation stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionHouseholderTran.getQR()
Inner matrix that stores the decomposition |
DenseMatrix64F |
QRDecompositionHouseholder.getQR()
Returns a single matrix which contains the combined values of Q and R. |
DenseMatrix64F |
QRDecompositionHouseholderColumn.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
DenseMatrix64F |
QRDecompositionBlock64.getR(DenseMatrix64F R,
boolean compact)
|
DenseMatrix64F |
QRDecompositionHouseholderTran.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
DenseMatrix64F |
QRDecompositionHouseholder.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
DenseMatrix64F |
QrUpdate.getU_tran()
|
| Methods in org.ejml.alg.dense.decomposition.qr with parameters of type DenseMatrix64F | |
|---|---|
void |
QrUpdate.addRow(DenseMatrix64F Q,
DenseMatrix64F R,
double[] row,
int rowIndex,
boolean resizeR)
Adjusts the values of the Q and R matrices to take in account the effects of inserting a row to the 'A' matrix at the specified location. |
void |
QRDecompositionHouseholderTran.applyQ(DenseMatrix64F A)
A = Q*A |
void |
QRDecompositionHouseholderTran.applyTranQ(DenseMatrix64F A)
A = QT*A |
protected void |
QRDecompositionHouseholder.commonSetup(DenseMatrix64F A)
This function performs sanity check on the input for decompose and sets up the QR matrix. |
protected void |
QRDecompositionHouseholderColumn.convertToColumnMajor(DenseMatrix64F A)
Converts the standard row-major matrix into a column-major vector that is advantageous for this problem. |
boolean |
QRDecompositionHouseholderColumn.decompose(DenseMatrix64F A)
To decompose the matrix 'A' it must have full rank. |
boolean |
QRColPivDecompositionHouseholderColumn.decompose(DenseMatrix64F A)
To decompose the matrix 'A' it must have full rank. |
boolean |
QRDecompositionHouseholderTran.decompose(DenseMatrix64F A)
To decompose the matrix 'A' it must have full rank. |
boolean |
QRDecompositionHouseholder.decompose(DenseMatrix64F A)
In order to decompose the matrix 'A' it must have full rank. |
void |
QrUpdate.deleteRow(DenseMatrix64F Q,
DenseMatrix64F R,
int rowIndex,
boolean resizeR)
Adjusts the values of the Q and R matrices to take in account the effects of removing a row from the 'A' matrix at the specified location. |
DenseMatrix64F |
QRColPivDecompositionHouseholderColumn.getPivotMatrix(DenseMatrix64F P)
|
DenseMatrix64F |
QRDecompositionHouseholderColumn.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the imformation stored in the QR matrix. |
DenseMatrix64F |
QRColPivDecompositionHouseholderColumn.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the information stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionBlock64.getQ(DenseMatrix64F Q,
boolean compact)
|
DenseMatrix64F |
QRDecompositionHouseholderTran.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the information stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionHouseholder.getQ(DenseMatrix64F Q,
boolean compact)
Computes the Q matrix from the imformation stored in the QR matrix. |
DenseMatrix64F |
QRDecompositionHouseholderColumn.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
DenseMatrix64F |
QRDecompositionBlock64.getR(DenseMatrix64F R,
boolean compact)
|
DenseMatrix64F |
QRDecompositionHouseholderTran.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
DenseMatrix64F |
QRDecompositionHouseholder.getR(DenseMatrix64F R,
boolean compact)
Returns an upper triangular matrix which is the R in the QR decomposition. |
static void |
QrHelperFunctions.rank1UpdateMultL(DenseMatrix64F A,
double[] u,
double gamma,
int colA0,
int w0,
int w1)
Performs a rank-1 update operation on the submatrix specified by w with the multiply on the left. A = A(I - γ*u*uT) |
static void |
QrHelperFunctions.rank1UpdateMultR(DenseMatrix64F A,
double[] u,
double gamma,
int colA0,
int w0,
int w1,
double[] _temp)
Performs a rank-1 update operation on the submatrix specified by w with the multiply on the right. A = (I - γ*u*uT)*A |
static void |
QrHelperFunctions.rank1UpdateMultR(DenseMatrix64F A,
double[] u,
int offsetU,
double gamma,
int colA0,
int w0,
int w1,
double[] _temp)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.svd |
|---|
| Methods in org.ejml.alg.dense.decomposition.svd that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
SvdImplicitQrDecompose.getU(boolean transpose)
|
DenseMatrix64F |
SvdImplicitQrDecompose.getV(boolean transpose)
|
DenseMatrix64F |
SvdImplicitQrDecompose.getW(DenseMatrix64F W)
|
| Methods in org.ejml.alg.dense.decomposition.svd with parameters of type DenseMatrix64F | |
|---|---|
boolean |
SvdImplicitQrDecompose.decompose(DenseMatrix64F orig)
|
DenseMatrix64F |
SvdImplicitQrDecompose.getW(DenseMatrix64F W)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.decomposition.svd.implicitqr |
|---|
| Fields in org.ejml.alg.dense.decomposition.svd.implicitqr declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
SvdImplicitQrAlgorithm.Ut
|
protected DenseMatrix64F |
SvdImplicitQrAlgorithm.Vt
|
| Methods in org.ejml.alg.dense.decomposition.svd.implicitqr that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
SvdImplicitQrAlgorithm.getUt()
|
DenseMatrix64F |
SvdImplicitQrAlgorithm.getVt()
|
| Methods in org.ejml.alg.dense.decomposition.svd.implicitqr with parameters of type DenseMatrix64F | |
|---|---|
void |
SvdImplicitQrAlgorithm.setUt(DenseMatrix64F ut)
|
void |
SvdImplicitQrAlgorithm.setVt(DenseMatrix64F vt)
|
protected void |
SvdImplicitQrAlgorithm.updateRotator(DenseMatrix64F Q,
int m,
int n,
double c,
double s)
Multiplied a transpose orthogonal matrix Q by the specified rotator. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol |
|---|
| Fields in org.ejml.alg.dense.linsol declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
LinearSolverAbstract.A
|
| Methods in org.ejml.alg.dense.linsol that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
LinearSolverAbstract.getA()
|
| Methods in org.ejml.alg.dense.linsol that return types with arguments of type DenseMatrix64F | |
|---|---|
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.general(int numRows,
int numCols)
Creates a general purpose solver. |
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.leastSquares(int numRows,
int numCols)
Creates a good general purpose solver for over determined systems and returns the optimal least-squares solution. |
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.leastSquaresQrPivot(boolean computeNorm2,
boolean computeQ)
Linear solver which uses QR pivot decomposition. |
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.linear(int matrixSize)
Creates a solver for linear systems. |
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.pseudoInverse(boolean useSVD)
Returns a solver which uses the pseudo inverse. |
static LinearSolver<DenseMatrix64F> |
LinearSolverFactory.symmPosDef(int matrixWidth)
Creates a solver for symmetric positive definite matrices. |
| Methods in org.ejml.alg.dense.linsol with parameters of type DenseMatrix64F | |
|---|---|
protected void |
LinearSolverAbstract._setA(DenseMatrix64F A)
|
void |
WrapLinearSolverBlock64.invert(DenseMatrix64F A_inv)
Creates a block matrix the same size as A_inv, inverts the matrix and copies the results back onto A_inv. |
void |
LinearSolverAbstract.invert(DenseMatrix64F A_inv)
|
void |
LinearSolverUnrolled.invert(DenseMatrix64F A_inv)
|
static void |
InvertUsingSolve.invert(LinearSolver<DenseMatrix64F> solver,
RowD1Matrix64F A,
DenseMatrix64F A_inv)
|
boolean |
WrapLinearSolverBlock64.setA(DenseMatrix64F A)
Converts 'A' into a block matrix and call setA() on the block matrix solver. |
boolean |
LinearSolverUnrolled.setA(DenseMatrix64F A)
|
void |
WrapLinearSolverBlock64.solve(DenseMatrix64F B,
DenseMatrix64F X)
Converts B and X into block matrices and calls the block matrix solve routine. |
void |
LinearSolverUnrolled.solve(DenseMatrix64F B,
DenseMatrix64F X)
|
| Method parameters in org.ejml.alg.dense.linsol with type arguments of type DenseMatrix64F | |
|---|---|
static void |
InvertUsingSolve.invert(LinearSolver<DenseMatrix64F> solver,
RowD1Matrix64F A,
DenseMatrix64F A_inv)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol.chol |
|---|
| Methods in org.ejml.alg.dense.linsol.chol with parameters of type DenseMatrix64F | |
|---|---|
void |
LinearSolverCholLDL.invert(DenseMatrix64F inv)
Sets the matrix 'inv' equal to the inverse of the matrix that was decomposed. |
void |
LinearSolverChol.invert(DenseMatrix64F inv)
Sets the matrix 'inv' equal to the inverse of the matrix that was decomposed. |
boolean |
LinearSolverCholLDL.setA(DenseMatrix64F A)
|
boolean |
LinearSolverChol.setA(DenseMatrix64F A)
|
void |
LinearSolverCholBlock64.solve(DenseMatrix64F B,
DenseMatrix64F X)
Only converts the B matrix and passes that onto solve. |
void |
LinearSolverCholLDL.solve(DenseMatrix64F B,
DenseMatrix64F X)
Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension. |
void |
LinearSolverChol.solve(DenseMatrix64F B,
DenseMatrix64F X)
Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol.gj |
|---|
| Methods in org.ejml.alg.dense.linsol.gj with parameters of type DenseMatrix64F | |
|---|---|
void |
GaussJordan.invert(DenseMatrix64F A)
|
void |
GaussJordanNoPivot.invert(DenseMatrix64F A)
|
boolean |
GaussJordan.setA(DenseMatrix64F A)
|
boolean |
GaussJordanNoPivot.setA(DenseMatrix64F A)
|
void |
GaussJordan.solve(DenseMatrix64F B,
DenseMatrix64F X)
Computes the inverse of matrix A and solves for X for each column in B. |
void |
GaussJordanNoPivot.solve(DenseMatrix64F B,
DenseMatrix64F X)
Computes the inverse of matrix A and solves for X for each column in B. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol.lu |
|---|
| Methods in org.ejml.alg.dense.linsol.lu with parameters of type DenseMatrix64F | |
|---|---|
void |
LinearSolverLuBase.improveSol(DenseMatrix64F b,
DenseMatrix64F x)
This attempts to improve upon the solution generated by account for numerical imprecisions. |
void |
LinearSolverLuBase.invert(DenseMatrix64F A_inv)
|
boolean |
LinearSolverLuKJI.setA(DenseMatrix64F A)
|
boolean |
LinearSolverLuBase.setA(DenseMatrix64F A)
|
void |
LinearSolverLuKJI.solve(DenseMatrix64F b,
DenseMatrix64F x)
An other implementation of solve() that processes the matrices in a different order. |
void |
LinearSolverLu.solve(DenseMatrix64F b,
DenseMatrix64F x)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol.qr |
|---|
| Fields in org.ejml.alg.dense.linsol.qr declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
BaseLinearSolverQrp.I
|
protected DenseMatrix64F |
LinearSolverQr.Q
|
protected DenseMatrix64F |
LinearSolverQr.R
|
protected DenseMatrix64F |
BaseLinearSolverQrp.R
|
protected DenseMatrix64F |
BaseLinearSolverQrp.R11
|
protected DenseMatrix64F |
BaseLinearSolverQrp.Y
|
| Fields in org.ejml.alg.dense.linsol.qr with type parameters of type DenseMatrix64F | |
|---|---|
protected LinearSolver<DenseMatrix64F> |
BaseLinearSolverQrp.internalSolver
|
| Methods in org.ejml.alg.dense.linsol.qr that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
AdjLinearSolverQr.getA()
Compute the A matrix from the Q and R matrices. |
| Methods in org.ejml.alg.dense.linsol.qr with parameters of type DenseMatrix64F | |
|---|---|
void |
BaseLinearSolverQrp.invert(DenseMatrix64F A_inv)
|
boolean |
LinearSolverQrHouseCol.setA(DenseMatrix64F A)
Performs QR decomposition on A |
boolean |
LinearSolverQrHouse.setA(DenseMatrix64F A)
Performs QR decomposition on A |
boolean |
LinearSolverQr.setA(DenseMatrix64F A)
Performs QR decomposition on A |
boolean |
LinearSolverQrHouseTran.setA(DenseMatrix64F A)
Performs QR decomposition on A |
boolean |
SolvePseudoInverseQrp.setA(DenseMatrix64F A)
|
boolean |
BaseLinearSolverQrp.setA(DenseMatrix64F A)
|
void |
LinearSolverQrHouseCol.solve(DenseMatrix64F B,
DenseMatrix64F X)
Solves for X using the QR decomposition. |
void |
LinearSolverQrHouse.solve(DenseMatrix64F B,
DenseMatrix64F X)
Solves for X using the QR decomposition. |
void |
LinearSolverQr.solve(DenseMatrix64F B,
DenseMatrix64F X)
Solves for X using the QR decomposition. |
void |
LinearSolverQrHouseTran.solve(DenseMatrix64F B,
DenseMatrix64F X)
Solves for X using the QR decomposition. |
void |
LinearSolverQrpHouseCol.solve(DenseMatrix64F B,
DenseMatrix64F X)
|
void |
SolvePseudoInverseQrp.solve(DenseMatrix64F B,
DenseMatrix64F X)
|
protected void |
BaseLinearSolverQrp.upgradeSolution(DenseMatrix64F X)
Upgrades the basic solution to the optimal 2-norm solution. |
| Constructor parameters in org.ejml.alg.dense.linsol.qr with type arguments of type DenseMatrix64F | |
|---|---|
BaseLinearSolverQrp(QRPDecomposition<DenseMatrix64F> decomposition,
boolean norm2Solution)
Configures internal parameters. |
|
LinearSolverQr(QRDecomposition<DenseMatrix64F> decomposer)
Creates a linear solver that uses QR decomposition. |
|
SolvePseudoInverseQrp(QRPDecomposition<DenseMatrix64F> decomposition,
boolean norm2Solution)
Configure and provide decomposition |
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.linsol.svd |
|---|
| Methods in org.ejml.alg.dense.linsol.svd with parameters of type DenseMatrix64F | |
|---|---|
void |
SolvePseudoInverseSvd.invert(DenseMatrix64F A_inv)
|
boolean |
SolvePseudoInverseSvd.setA(DenseMatrix64F A)
|
void |
SolvePseudoInverseSvd.solve(DenseMatrix64F b,
DenseMatrix64F x)
|
| Uses of DenseMatrix64F in org.ejml.alg.dense.misc |
|---|
| Methods in org.ejml.alg.dense.misc with parameters of type DenseMatrix64F | |
|---|---|
static void |
ImplCommonOps_DenseMatrix64F.extract(DenseMatrix64F src,
int srcY0,
int srcX0,
DenseMatrix64F dst,
int dstY0,
int dstX0,
int numRows,
int numCols)
|
static void |
UnrolledInverseFromMinor.inv(DenseMatrix64F mat,
DenseMatrix64F inv)
|
static void |
UnrolledInverseFromMinor.inv2(DenseMatrix64F mat,
DenseMatrix64F inv,
double scale)
|
static void |
UnrolledInverseFromMinor.inv3(DenseMatrix64F mat,
DenseMatrix64F inv,
double scale)
|
static void |
UnrolledInverseFromMinor.inv4(DenseMatrix64F mat,
DenseMatrix64F inv,
double scale)
|
static void |
UnrolledInverseFromMinor.inv5(DenseMatrix64F mat,
DenseMatrix64F inv,
double scale)
|
static double |
NaiveDeterminant.leibniz(DenseMatrix64F mat)
Computes the determinant of the matrix using Leibniz's formula |
static double |
NaiveDeterminant.recursive(DenseMatrix64F mat)
A simple and inefficient algorithm for computing the determinant. |
| Uses of DenseMatrix64F in org.ejml.alg.dense.mult |
|---|
| Methods in org.ejml.alg.dense.mult with parameters of type DenseMatrix64F | |
|---|---|
static void |
VectorVectorMult.mult(DenseMatrix64F x,
DenseMatrix64F y,
DenseMatrix64F A)
|
static void |
VectorVectorMult.rank1Update(double gamma,
DenseMatrix64F A,
DenseMatrix64F u,
DenseMatrix64F w)
Performs a rank one update on matrix A using vectors u and w. |
static void |
VectorVectorMult.rank1Update(double gamma,
DenseMatrix64F A,
DenseMatrix64F u,
DenseMatrix64F w,
DenseMatrix64F B)
Performs a rank one update on matrix A using vectors u and w. |
| Uses of DenseMatrix64F in org.ejml.data |
|---|
| Fields in org.ejml.data declared as DenseMatrix64F | |
|---|---|
DenseMatrix64F |
Eigenpair.vector
|
| Methods in org.ejml.data that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
DenseMatrix64F.copy()
Creates and returns a matrix which is idential to this one. |
static DenseMatrix64F |
DenseMatrix64F.wrap(int numRows,
int numCols,
double[] data)
Creates a new DenseMatrix64F around the provided data. |
| Methods in org.ejml.data with parameters of type DenseMatrix64F | |
|---|---|
void |
DenseMatrix64F.setReshape(DenseMatrix64F b)
Sets the value and shape of this matrix to be identical to the specified matrix. |
| Constructors in org.ejml.data with parameters of type DenseMatrix64F | |
|---|---|
DenseMatrix64F(DenseMatrix64F orig)
Creates a new matrix which is equivalent to the provided matrix. |
|
Eigenpair(double value,
DenseMatrix64F vector)
|
|
| Uses of DenseMatrix64F in org.ejml.ops |
|---|
| Methods in org.ejml.ops that return DenseMatrix64F | |
|---|---|
static DenseMatrix64F[] |
CommonOps.columnsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the columns in a matrix into a set of vectors. |
static DenseMatrix64F |
SpecializedOps.copyChangeRow(int[] order,
DenseMatrix64F src,
DenseMatrix64F dst)
Creates a copy of a matrix but swaps the rows as specified by the order array. |
static DenseMatrix64F |
SpecializedOps.copyTriangle(DenseMatrix64F src,
DenseMatrix64F dst,
boolean upper)
Copies just the upper or lower triangular portion of a matrix. |
static DenseMatrix64F |
RandomMatrices.createDiagonal(int N,
double min,
double max,
Random rand)
Creates a random diagonal matrix where the diagonal elements are selected from a uniform distribution that goes from min to max. |
static DenseMatrix64F |
RandomMatrices.createDiagonal(int numRows,
int numCols,
double min,
double max,
Random rand)
Creates a random matrix where all elements are zero but diagonal elements. |
static DenseMatrix64F |
RandomMatrices.createEigenvaluesSymm(int num,
Random rand,
double... eigenvalues)
Creates a new random symmetric matrix that will have the specified real eigenvalues. |
static DenseMatrix64F |
RandomMatrices.createInSpan(DenseMatrix64F[] span,
double min,
double max,
Random rand)
Creates a random vector that is inside the specified span. |
static DenseMatrix64F |
EigenOps.createMatrixD(EigenDecomposition eig)
A diagonal matrix where real diagonal element contains a real eigenvalue. |
static DenseMatrix64F |
EigenOps.createMatrixV(EigenDecomposition<DenseMatrix64F> eig)
Puts all the real eigenvectors into the columns of a matrix. |
static DenseMatrix64F |
RandomMatrices.createOrthogonal(int numRows,
int numCols,
Random rand)
Creates a random orthogonal or isometric matrix, depending on the number of rows and columns. |
static DenseMatrix64F |
RandomMatrices.createRandom(int numRow,
int numCol,
double min,
double max,
Random rand)
Returns a matrix where all the elements are selected independently from a uniform distribution between 'min' and 'max' inclusive. |
static DenseMatrix64F |
RandomMatrices.createRandom(int numRow,
int numCol,
Random rand)
Returns a matrix where all the elements are selected independently from a uniform distribution between 0 and 1 inclusive. |
static DenseMatrix64F |
SpecializedOps.createReflector(DenseMatrix64F u,
double gamma)
Creates a reflector from the provided vector and gamma. Q = I - γ u uT |
static DenseMatrix64F |
SpecializedOps.createReflector(RowD1Matrix64F u)
Creates a reflector from the provided vector. Q = I - γ u uT γ = 2/||u||2 |
static DenseMatrix64F |
RandomMatrices.createSingularValues(int numRows,
int numCols,
Random rand,
double... sv)
Creates a random matrix which will have the provided singular values. |
static DenseMatrix64F[] |
RandomMatrices.createSpan(int dimen,
int numVectors,
Random rand)
Creates a randomly generated set of orthonormal vectors. |
static DenseMatrix64F |
RandomMatrices.createSymmetric(int length,
double min,
double max,
Random rand)
Creates a random symmetric matrix whose values are selected from an uniform distribution from min to max, inclusive. |
static DenseMatrix64F |
RandomMatrices.createSymmPosDef(int width,
Random rand)
Creates a random symmetric positive definite matrix. |
static DenseMatrix64F |
RandomMatrices.createUpperTriangle(int dimen,
int hessenberg,
double min,
double max,
Random rand)
Creates an upper triangular matrix whose values are selected from a uniform distribution. |
static DenseMatrix64F |
CommonOps.diag(DenseMatrix64F ret,
int width,
double... diagEl)
|
static DenseMatrix64F |
CommonOps.diag(double... diagEl)
Creates a new square matrix whose diagonal elements are specified by diagEl and all the other elements are zero. aij = 0 if i ≤ j aij = diag[i] if i = j |
static DenseMatrix64F |
CommonOps.diagR(int numRows,
int numCols,
double... diagEl)
Creates a new rectangular matrix whose diagonal elements are specified by diagEl and all the other elements are zero. aij = 0 if i ≤ j aij = diag[i] if i = j |
static DenseMatrix64F |
CommonOps.extract(DenseMatrix64F src,
int srcY0,
int srcY1,
int srcX0,
int srcX1)
Creates a new matrix which is the specified submatrix of 'src' |
static DenseMatrix64F |
CommonOps.identity(int width)
Creates an identity matrix of the specified size. aij = 0 if i ≠ j aij = 1 if i = j |
static DenseMatrix64F |
CommonOps.identity(int numRows,
int numCols)
Creates a rectangular matrix which is zero except along the diagonals. |
static DenseMatrix64F |
MatrixIO.loadCSV(String fileName)
Reads a matrix in which has been encoded using a Column Space Value (CSV) file format. |
static DenseMatrix64F |
MatrixIO.loadCSV(String fileName,
int numRows,
int numCols)
Reads a matrix in which has been encoded using a Column Space Value (CSV) file format. |
static DenseMatrix64F |
SingularOps.nullSpace(SingularValueDecomposition<DenseMatrix64F> svd,
DenseMatrix64F v)
Computes the null space from the provided singular value. |
static DenseMatrix64F |
SpecializedOps.pivotMatrix(DenseMatrix64F ret,
int[] pivots,
int numPivots,
boolean transposed)
Creates a pivot matrix that exchanges the rows in a matrix: A' = P*A |
DenseMatrix64F |
ReadMatrixCsv.read()
Reads in a DenseMatrix64F from the IO stream. |
DenseMatrix64F |
ReadMatrixCsv.read(int numRows,
int numCols)
|
static DenseMatrix64F[] |
CommonOps.rowsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the rows in a matrix into a set of vectors. |
static DenseMatrix64F[] |
SpecializedOps.splitIntoVectors(RowD1Matrix64F A,
boolean column)
Takes a matrix and splits it into a set of row or column vectors. |
static DenseMatrix64F |
CommonOps.sumCols(DenseMatrix64F input,
DenseMatrix64F output)
Computes the sum of each column in the input matrix and returns the results in a vector: bj = sum(i=1:m ; |aij|) |
static DenseMatrix64F |
CommonOps.sumRows(DenseMatrix64F input,
DenseMatrix64F output)
Computes the sum of each row in the input matrix and returns the results in a vector: bj = sum(i=1:n ; |aji|) |
static DenseMatrix64F |
CommonOps.transpose(DenseMatrix64F A,
DenseMatrix64F A_tran)
Transposes matrix 'a' and stores the results in 'b': bij = aji where 'b' is the transpose of 'a'. |
| Methods in org.ejml.ops with parameters of type DenseMatrix64F | |
|---|---|
static void |
RandomMatrices.addRandom(DenseMatrix64F A,
double min,
double max,
Random rand)
Adds random values to each element in the matrix from an uniform distribution. aij = aij + U(min,max) |
static double[] |
EigenOps.boundLargestEigenValue(DenseMatrix64F A,
double[] bound)
Generates a bound for the largest eigen value of the provided matrix using Perron-Frobenius theorem. |
static void |
SingularOps.checkSvdMatrixSize(DenseMatrix64F U,
boolean tranU,
DenseMatrix64F W,
DenseMatrix64F V,
boolean tranV)
Checks to see if all the provided matrices are the expected size for an SVD. |
static DenseMatrix64F[] |
CommonOps.columnsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the columns in a matrix into a set of vectors. |
static DenseMatrix64F[] |
CommonOps.columnsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the columns in a matrix into a set of vectors. |
static double |
EigenOps.computeEigenValue(DenseMatrix64F A,
DenseMatrix64F eigenVector)
Given matrix A and an eigen vector of A, compute the corresponding eigen value. |
static Eigenpair |
EigenOps.computeEigenVector(DenseMatrix64F A,
double eigenvalue)
Given an eigenvalue it computes an eigenvector using inverse iteration: for i=1:MAX { (A - μI)z(i) = q(i-1) q(i) = z(i) / ||z(i)|| λ(i) = q(i)T A q(i) } |
static double |
NormOps.conditionP(DenseMatrix64F A,
double p)
The condition number of a matrix is used to measure the sensitivity of the linear system Ax=b. |
static double |
NormOps.conditionP2(DenseMatrix64F A)
The condition p = 2 number of a matrix is used to measure the sensitivity of the linear system Ax=b. |
static DenseMatrix64F |
SpecializedOps.copyChangeRow(int[] order,
DenseMatrix64F src,
DenseMatrix64F dst)
Creates a copy of a matrix but swaps the rows as specified by the order array. |
static DenseMatrix64F |
SpecializedOps.copyTriangle(DenseMatrix64F src,
DenseMatrix64F dst,
boolean upper)
Copies just the upper or lower triangular portion of a matrix. |
static DenseMatrix64F |
RandomMatrices.createInSpan(DenseMatrix64F[] span,
double min,
double max,
Random rand)
Creates a random vector that is inside the specified span. |
static DenseMatrix64F |
SpecializedOps.createReflector(DenseMatrix64F u,
double gamma)
Creates a reflector from the provided vector and gamma. Q = I - γ u uT |
static void |
RandomMatrices.createSymmetric(DenseMatrix64F A,
double min,
double max,
Random rand)
Sets the provided square matrix to be a random symmetric matrix whose values are selected from an uniform distribution from min to max, inclusive. |
static void |
SingularOps.descendingOrder(DenseMatrix64F U,
boolean tranU,
DenseMatrix64F W,
DenseMatrix64F V,
boolean tranV)
Adjusts the matrices so that the singular values are in descending order. |
static void |
SingularOps.descendingOrder(DenseMatrix64F U,
boolean tranU,
double[] singularValues,
int numSingularValues,
DenseMatrix64F V,
boolean tranV)
Similar to SingularOps.descendingOrder(org.ejml.data.DenseMatrix64F, boolean, org.ejml.data.DenseMatrix64F, org.ejml.data.DenseMatrix64F, boolean)
but takes in an array of singular values instead. |
static double |
CommonOps.det(DenseMatrix64F mat)
Returns the determinant of the matrix. |
static DenseMatrix64F |
CommonOps.diag(DenseMatrix64F ret,
int width,
double... diagEl)
|
static Eigenpair |
EigenOps.dominantEigenpair(DenseMatrix64F A)
Computes the dominant eigen vector for a matrix. |
static DenseMatrix64F |
CommonOps.extract(DenseMatrix64F src,
int srcY0,
int srcY1,
int srcX0,
int srcX1)
Creates a new matrix which is the specified submatrix of 'src' |
static void |
CommonOps.extractDiag(DenseMatrix64F src,
DenseMatrix64F dst)
Extracts the diagonal elements 'src' write it to the 'dst' vector. |
static double |
NormOps.fastNormP(DenseMatrix64F A,
double p)
An unsafe but faster version of NormOps.normP(org.ejml.data.DenseMatrix64F, double) that calls routines which are faster
but more prone to overflow/underflow problems. |
static double |
NormOps.fastNormP2(DenseMatrix64F A)
Computes the p=2 norm. |
static double |
NormOps.inducedP1(DenseMatrix64F A)
Computes the induced p = 1 matrix norm. ||A||1= max(j=1 to n; sum(i=1 to m; |aij|)) |
static double |
NormOps.inducedP2(DenseMatrix64F A)
Computes the induced p = 2 matrix norm, which is the largest singular value. |
static double |
NormOps.inducedPInf(DenseMatrix64F A)
Induced matrix p = infinity norm. ||A||∞ = max(i=1 to m; sum(j=1 to n; |aij|)) |
static boolean |
CommonOps.invert(DenseMatrix64F mat)
Performs a matrix inversion operation on the specified matrix and stores the results in the same matrix. a = a-1 |
static boolean |
CovarianceOps.invert(DenseMatrix64F cov)
Performs a matrix inversion operations that takes advantage of the special properties of a covariance matrix. |
static boolean |
CommonOps.invert(DenseMatrix64F mat,
DenseMatrix64F result)
Performs a matrix inversion operation that does not modify the original and stores the results in another matrix. |
static boolean |
CovarianceOps.invert(DenseMatrix64F cov,
DenseMatrix64F cov_inv)
Performs a matrix inversion operations that takes advantage of the special properties of a covariance matrix. |
static boolean |
MatrixFeatures.isConstantVal(DenseMatrix64F mat,
double val,
double tol)
Checks to see if every value in the matrix is the specified value. |
static boolean |
MatrixFeatures.isDiagonalPositive(DenseMatrix64F a)
Checks to see if all the diagonal elements in the matrix are positive. |
static boolean |
MatrixFeatures.isFullRank(DenseMatrix64F a)
|
static boolean |
MatrixFeatures.isIdentity(DenseMatrix64F mat,
double tol)
Checks to see if the provided matrix is within tolerance to an identity matrix. |
static boolean |
MatrixFeatures.isInverse(DenseMatrix64F a,
DenseMatrix64F b,
double tol)
Checks to see if the two matrices are inverses of each other. |
static boolean |
MatrixFeatures.isOrthogonal(DenseMatrix64F Q,
double tol)
Checks to see if a matrix is orthogonal or isometric. |
static boolean |
MatrixFeatures.isPositiveDefinite(DenseMatrix64F A)
Checks to see if the matrix is positive definite. |
static boolean |
MatrixFeatures.isPositiveSemidefinite(DenseMatrix64F A)
Checks to see if the matrix is positive semidefinite: |
static boolean |
MatrixFeatures.isRowsLinearIndependent(DenseMatrix64F A)
Checks to see if the rows of the provided matrix are linearly independent. |
static boolean |
MatrixFeatures.isSkewSymmetric(DenseMatrix64F A,
double tol)
Checks to see if a matrix is skew symmetric with in tolerance: -A = AT or |aij + aji| ≤ tol |
static boolean |
MatrixFeatures.isSymmetric(DenseMatrix64F m)
Returns true if the matrix is perfectly symmetric. |
static boolean |
MatrixFeatures.isSymmetric(DenseMatrix64F m,
double tol)
Returns true if the matrix is symmetric within the tolerance. |
static boolean |
MatrixFeatures.isUpperTriangle(DenseMatrix64F A,
int hessenberg,
double tol)
Checks to see if a matrix is upper triangular or Hessenberg. |
static int |
CovarianceOps.isValid(DenseMatrix64F cov)
Performs a variety of tests to see if the provided matrix is a valid covariance matrix. |
static boolean |
CovarianceOps.isValidFast(DenseMatrix64F cov)
This is a fairly light weight check to see of a covariance matrix is valid. |
static void |
CommonOps.kron(DenseMatrix64F A,
DenseMatrix64F B,
DenseMatrix64F C)
The Kronecker product of two matrices is defined as: Cij = aijB where Cij is a sub matrix inside of C ∈ ℜ m*k × n*l, A ∈ ℜ m × n, and B ∈ ℜ k × l. |
void |
CovarianceRandomDraw.next(DenseMatrix64F x)
Makes a draw on the distribution. |
static void |
NormOps.normalizeF(DenseMatrix64F A)
Normalizes the matrix such that the Frobenius norm is equal to one. |
static double |
NormOps.normP(DenseMatrix64F A,
double p)
Computes either the vector p-norm or the induced matrix p-norm depending on A being a vector or a matrix respectively. |
static double |
NormOps.normP1(DenseMatrix64F A)
Computes the p=1 norm. |
static double |
NormOps.normP2(DenseMatrix64F A)
Computes the p=2 norm. |
static double |
NormOps.normPInf(DenseMatrix64F A)
Computes the p=∞ norm. |
static int |
MatrixFeatures.nullity(DenseMatrix64F A)
Computes the nullity of a matrix using the default tolerance. |
static int |
MatrixFeatures.nullity(DenseMatrix64F A,
double threshold)
Computes the nullity of a matrix using the specified tolerance. |
static DenseMatrix64F |
SingularOps.nullSpace(SingularValueDecomposition<DenseMatrix64F> svd,
DenseMatrix64F v)
Computes the null space from the provided singular value. |
static void |
CommonOps.pinv(DenseMatrix64F A,
DenseMatrix64F invA)
Computes the Moore-Penrose pseudo-inverse: pinv(A) = (ATA)-1 AT or pinv(A) = AT(AAT)-1 |
static DenseMatrix64F |
SpecializedOps.pivotMatrix(DenseMatrix64F ret,
int[] pivots,
int numPivots,
boolean transposed)
Creates a pivot matrix that exchanges the rows in a matrix: A' = P*A |
static void |
CovarianceOps.randomVector(DenseMatrix64F cov,
DenseMatrix64F vector,
Random rand)
Sets vector to a random value based upon a zero-mean multivariate Gaussian distribution with covariance 'cov'. |
static int |
MatrixFeatures.rank(DenseMatrix64F A)
Computes the rank of a matrix using a default tolerance. |
static int |
MatrixFeatures.rank(DenseMatrix64F A,
double threshold)
Computes the rank of a matrix using the specified tolerance. |
static DenseMatrix64F[] |
CommonOps.rowsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the rows in a matrix into a set of vectors. |
static DenseMatrix64F[] |
CommonOps.rowsToVector(DenseMatrix64F A,
DenseMatrix64F[] v)
Converts the rows in a matrix into a set of vectors. |
static void |
RandomMatrices.setRandom(DenseMatrix64F mat,
Random rand)
Sets each element in the matrix to a value drawn from an uniform distribution from 0 to 1 inclusive. |
static boolean |
CommonOps.solve(DenseMatrix64F a,
DenseMatrix64F b,
DenseMatrix64F x)
Solves for x in the following equation: A*x = b |
static DenseMatrix64F |
CommonOps.sumCols(DenseMatrix64F input,
DenseMatrix64F output)
Computes the sum of each column in the input matrix and returns the results in a vector: bj = sum(i=1:m ; |aij|) |
static DenseMatrix64F |
CommonOps.sumRows(DenseMatrix64F input,
DenseMatrix64F output)
Computes the sum of each row in the input matrix and returns the results in a vector: bj = sum(i=1:n ; |aji|) |
static void |
CommonOps.transpose(DenseMatrix64F mat)
Performs an in-place transpose. |
static DenseMatrix64F |
CommonOps.transpose(DenseMatrix64F A,
DenseMatrix64F A_tran)
Transposes matrix 'a' and stores the results in 'b': bij = aji where 'b' is the transpose of 'a'. |
| Method parameters in org.ejml.ops with type arguments of type DenseMatrix64F | |
|---|---|
static DenseMatrix64F |
EigenOps.createMatrixV(EigenDecomposition<DenseMatrix64F> eig)
Puts all the real eigenvectors into the columns of a matrix. |
static DenseMatrix64F |
SingularOps.nullSpace(SingularValueDecomposition<DenseMatrix64F> svd,
DenseMatrix64F v)
Computes the null space from the provided singular value. |
| Constructors in org.ejml.ops with parameters of type DenseMatrix64F | |
|---|---|
CovarianceRandomDraw(Random rand,
DenseMatrix64F cov)
Creates a random distribution with the specified mean and covariance. |
|
| Uses of DenseMatrix64F in org.ejml.simple |
|---|
| Fields in org.ejml.simple declared as DenseMatrix64F | |
|---|---|
protected DenseMatrix64F |
SimpleBase.mat
Internal matrix which this is a wrapper around. |
| Methods in org.ejml.simple that return DenseMatrix64F | |
|---|---|
DenseMatrix64F |
SimpleBase.getMatrix()
Returns a reference to the matrix that it uses internally. |
| Methods in org.ejml.simple with parameters of type DenseMatrix64F | |
|---|---|
static SimpleMatrix |
SimpleMatrix.wrap(DenseMatrix64F internalMat)
Creates a new SimpleMatrix with the specified DenseMatrix64F used as its internal matrix. |
| Constructors in org.ejml.simple with parameters of type DenseMatrix64F | |
|---|---|
SimpleEVD(DenseMatrix64F mat)
|
|
SimpleMatrix(DenseMatrix64F orig)
Creates a new SimpleMatrix which is a copy of the DenseMatrix64F. |
|
SimpleSVD(DenseMatrix64F mat,
boolean compact)
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