Inheritance diagram for Eigen::CoeffBasedProduct:

[legend]

Public Types

typedef MatrixBase
< CoeffBasedProduct > Base

typedef Base::PlainObject PlainObject

The plain matrix type corresponding to this expression.

enum

typedef Diagonal< Derived > DiagonalReturnType

typedef const Diagonal< const
Derived > ConstDiagonalReturnType

typedef Homogeneous< Derived,
HomogeneousReturnTypeDirection > HomogeneousReturnType

typedef Block< const Derived,
internal::traits< Derived >
::ColsAtCompileTime==1?SizeMinusOne:1,
internal::traits< Derived >
::ColsAtCompileTime==1?1:SizeMinusOne > ConstStartMinusOne

typedef CwiseUnaryOp
< internal::scalar_quotient1_op
< typename internal::traits
< Derived >::Scalar >, const
ConstStartMinusOne > HNormalizedReturnType

typedef
internal::stem_function
< Scalar >::type StemFunction

MRPT plugin: Types

enum

typedef Scalar value_type

Type of the elements.

Public Member Functions

CoeffBasedProduct (const CoeffBasedProduct &other)

template<typename Lhs , typename Rhs >

CoeffBasedProduct (const Lhs &lhs, const Rhs &rhs)

EIGEN_STRONG_INLINE Index rows () const

EIGEN_STRONG_INLINE Index cols () const

EIGEN_STRONG_INLINE const Scalar coeff (Index row, Index col) const

EIGEN_STRONG_INLINE const Scalar coeff (Index index) const

template<int LoadMode>

EIGEN_STRONG_INLINE const
PacketScalar packet (Index row, Index col) const

EIGEN_STRONG_INLINE operator const PlainObject & () const

const _LhsNested & lhs () const

const _RhsNested & rhs () const

const Diagonal< const
LazyCoeffBasedProductType, 0 > diagonal () const

template<int DiagonalIndex>

const Diagonal< const
LazyCoeffBasedProductType,
DiagonalIndex > diagonal () const

const Diagonal< const
LazyCoeffBasedProductType,
Dynamic > diagonal (Index index) const

Index diagonalSize () const

const CwiseUnaryOp
< internal::scalar_opposite_op
< typename internal::traits
< Derived >::Scalar >, const
Derived > operator- () const

const ScalarMultipleReturnType operator* (const Scalar &scalar) const

const ScalarMultipleReturnType operator* (const RealScalar &scalar) const

const CwiseUnaryOp
< internal::scalar_multiple2_op
< Scalar, std::complex< Scalar >
>, const Derived > operator* (const std::complex< Scalar > &scalar) const

Overloaded for efficient real matrix times complex scalar value.

const ProductReturnType
< Derived, OtherDerived >
::Type operator* (const MatrixBase< OtherDerived > &other) const

const DiagonalProduct< Derived,
DiagonalDerived, OnTheRight > operator* (const DiagonalBase< DiagonalDerived > &diagonal) const

ScalarMultipleReturnType operator* (const UniformScaling< Scalar > &s) const

const CwiseUnaryOp
< internal::scalar_quotient1_op
< typename internal::traits
< Derived >::Scalar >, const
Derived > operator/ (const Scalar &scalar) const

internal::cast_return_type
< Derived, const CwiseUnaryOp
< internal::scalar_cast_op
< typename internal::traits
< Derived >::Scalar, NewType >
, const Derived > >::type cast () const

ConjugateReturnType conjugate () const

RealReturnType real () const

NonConstRealReturnType real ()

const ImagReturnType imag () const

NonConstImagReturnType imag ()

const CwiseUnaryOp
< CustomUnaryOp, const Derived > unaryExpr (const CustomUnaryOp &func=CustomUnaryOp()) const

Apply a unary operator coefficient-wise.

const CwiseUnaryView
< CustomViewOp, const Derived > unaryViewExpr (const CustomViewOp &func=CustomViewOp()) const

EIGEN_STRONG_INLINE const
CwiseBinaryOp< CustomBinaryOp,
const Derived, const
OtherDerived > binaryExpr (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other, const CustomBinaryOp &func=CustomBinaryOp()) const

EIGEN_STRONG_INLINE const
CwiseUnaryOp
< internal::scalar_abs_op
< Scalar >, const Derived > cwiseAbs () const

EIGEN_STRONG_INLINE const
CwiseUnaryOp
< internal::scalar_abs2_op
< Scalar >, const Derived > cwiseAbs2 () const

const CwiseUnaryOp
< internal::scalar_sqrt_op
< Scalar >, const Derived > cwiseSqrt () const

const CwiseUnaryOp
< internal::scalar_inverse_op
< Scalar >, const Derived > cwiseInverse () const

const CwiseUnaryOp
< std::binder1st
< std::equal_to< Scalar >
>, const Derived > cwiseEqual (const Scalar &s) const

const CwiseBinaryOp
< std::equal_to< Scalar >
, const Derived, const
OtherDerived > cwiseEqual (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE (Derived, OtherDerived) cwiseProduct(const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

const CwiseBinaryOp
< std::not_equal_to< Scalar >
, const Derived, const
OtherDerived > cwiseNotEqual (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

EIGEN_STRONG_INLINE const
CwiseBinaryOp
< internal::scalar_min_op
< Scalar >, const Derived,
const OtherDerived > cwiseMin (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

EIGEN_STRONG_INLINE const
CwiseBinaryOp
< internal::scalar_max_op
< Scalar >, const Derived,
const OtherDerived > cwiseMax (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

EIGEN_STRONG_INLINE const
CwiseBinaryOp
< internal::scalar_quotient_op
< Scalar >, const Derived,
const OtherDerived > cwiseQuotient (const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &other) const

bool isDiagonal (RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

void normalize ()

EIGEN_STRONG_INLINE void extractRow (size_t nRow, Eigen::EigenBase< OtherDerived > &v, size_t startingCol=0) const

Extract one row from the matrix into a row vector.

void extractRow (size_t nRow, std::vector< T > &v, size_t startingCol=0) const

EIGEN_STRONG_INLINE void extractRowAsCol (size_t nRow, VECTOR &v, size_t startingCol=0) const

Extract one row from the matrix into a column vector.

EIGEN_STRONG_INLINE void extractCol (size_t nCol, VECTOR &v, size_t startingRow=0) const

Extract one column from the matrix into a column vector.

void extractCol (size_t nCol, std::vector< T > &v, size_t startingRow=0) const

EIGEN_STRONG_INLINE void extractMatrix (const size_t firstRow, const size_t firstCol, MATRIX &m) const

EIGEN_STRONG_INLINE void extractMatrix (const size_t firstRow, const size_t firstCol, const size_t nRows, const size_t nCols, MATRIX &m) const

EIGEN_STRONG_INLINE void extractSubmatrix (const size_t row_first, const size_t row_last, const size_t col_first, const size_t col_last, MATRIX &out) const

Get a submatrix, given its bounds: first & last column and row (inclusive).

void extractSubmatrixSymmetricalBlocks (const size_t block_size, const std::vector< size_t > &block_indices, MATRIX &out) const

Get a submatrix from a square matrix, by collecting the elements M(idxs,idxs), where idxs is a sequence {block_indices(i):block_indices(i)+block_size-1} for all "i" up to the size of block_indices.

void extractSubmatrixSymmetrical (const std::vector< size_t > &indices, MATRIX &out) const

Get a submatrix from a square matrix, by collecting the elements M(idxs,idxs), where idxs is the sequence of indices passed as argument.

Derived & operator+= (const MatrixBase< OtherDerived > &other)

Derived & operator-= (const MatrixBase< OtherDerived > &other)

const LazyProductReturnType
< Derived, OtherDerived >
::Type lazyProduct (const MatrixBase< OtherDerived > &other) const

Derived & operator*= (const EigenBase< OtherDerived > &other)

void applyOnTheLeft (const EigenBase< OtherDerived > &other)

void applyOnTheLeft (Index p, Index q, const JacobiRotation< OtherScalar > &j)

void applyOnTheRight (const EigenBase< OtherDerived > &other)

void applyOnTheRight (Index p, Index q, const JacobiRotation< OtherScalar > &j)

internal::scalar_product_traits
< typename internal::traits
< Derived >::Scalar, typename
internal::traits< OtherDerived >
::Scalar >::ReturnType dot (const MatrixBase< OtherDerived > &other) const

RealScalar squaredNorm () const

RealScalar norm () const

RealScalar stableNorm () const

RealScalar blueNorm () const

RealScalar hypotNorm () const

const PlainObject normalized () const

const AdjointReturnType adjoint () const

void adjointInPlace ()

DiagonalReturnType diagonal ()

DiagonalIndexReturnType
< Dynamic >::Type diagonal (Index index)

TriangularViewReturnType< Mode >
::Type triangularView ()

ConstTriangularViewReturnType
< Mode >::Type triangularView () const

SelfAdjointViewReturnType
< UpLo >::Type selfadjointView ()

ConstSelfAdjointViewReturnType
< UpLo >::Type selfadjointView () const

const SparseView< Derived > sparseView (const Scalar &m_reference=Scalar(0), typename NumTraits< Scalar >::Real m_epsilon=NumTraits< Scalar >::dummy_precision()) const

const DiagonalWrapper< const
Derived > asDiagonal () const

const PermutationWrapper
< const Derived > asPermutation () const

Derived & setIdentity ()

Derived & setIdentity (Index rows, Index cols)

bool isIdentity (RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

bool isUpperTriangular (RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

bool isLowerTriangular (RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

bool isOrthogonal (const MatrixBase< OtherDerived > &other, RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

bool isUnitary (RealScalar prec=NumTraits< Scalar >::dummy_precision()) const

bool operator== (const MatrixBase< OtherDerived > &other) const

bool operator!= (const MatrixBase< OtherDerived > &other) const

NoAlias< Derived,
Eigen::MatrixBase > noalias ()

const ForceAlignedAccess< Derived > forceAlignedAccess () const

ForceAlignedAccess< Derived > forceAlignedAccess ()

internal::add_const_on_value_type
< typename
internal::conditional< Enable,
ForceAlignedAccess< Derived >
, Derived & >::type >::type forceAlignedAccessIf () const

internal::conditional< Enable,
ForceAlignedAccess< Derived >
, Derived & >::type forceAlignedAccessIf ()

Scalar trace () const

RealScalar lpNorm () const

MatrixBase< Derived > & matrix ()

const MatrixBase< Derived > & matrix () const

ArrayWrapper< Derived > array ()

const ArrayWrapper< Derived > array () const

const FullPivLU< PlainObject > fullPivLu () const

const PartialPivLU< PlainObject > partialPivLu () const

const PartialPivLU< PlainObject > lu () const

const internal::inverse_impl
< Derived > inverse () const

void computeInverseAndDetWithCheck (ResultType &inverse, typename ResultType::Scalar &determinant, bool &invertible, const RealScalar &absDeterminantThreshold=NumTraits< Scalar >::dummy_precision()) const

void computeInverseWithCheck (ResultType &inverse, bool &invertible, const RealScalar &absDeterminantThreshold=NumTraits< Scalar >::dummy_precision()) const

Scalar determinant () const

const LLT< PlainObject > llt () const

const LDLT< PlainObject > ldlt () const

const HouseholderQR< PlainObject > householderQr () const

const ColPivHouseholderQR
< PlainObject > colPivHouseholderQr () const

const FullPivHouseholderQR
< PlainObject > fullPivHouseholderQr () const

EigenvaluesReturnType eigenvalues () const

RealScalar operatorNorm () const

JacobiSVD< PlainObject > jacobiSvd (unsigned int computationOptions=0) const

cross_product_return_type
< OtherDerived >::type cross (const MatrixBase< OtherDerived > &other) const

PlainObject cross3 (const MatrixBase< OtherDerived > &other) const

PlainObject unitOrthogonal (void) const

Matrix< Scalar, 3, 1 > eulerAngles (Index a0, Index a1, Index a2) const

HomogeneousReturnType homogeneous () const

const HNormalizedReturnType hnormalized () const

void makeHouseholderInPlace (Scalar &tau, RealScalar &beta)

void makeHouseholder (EssentialPart &essential, Scalar &tau, RealScalar &beta) const

void applyHouseholderOnTheLeft (const EssentialPart &essential, const Scalar &tau, Scalar *workspace)

void applyHouseholderOnTheRight (const EssentialPart &essential, const Scalar &tau, Scalar *workspace)

const
MatrixExponentialReturnValue
< Derived > exp () const

const
MatrixFunctionReturnValue
< Derived > matrixFunction (StemFunction f) const

const
MatrixFunctionReturnValue
< Derived > cosh () const

const
MatrixFunctionReturnValue
< Derived > sinh () const

const
MatrixFunctionReturnValue
< Derived > cos () const

const
MatrixFunctionReturnValue
< Derived > sin () const

const
MatrixSquareRootReturnValue
< Derived > sqrt () const

const
MatrixLogarithmReturnValue
< Derived > log () const

MRPT plugin: Set/get/load/save and other miscelaneous methods

EIGEN_STRONG_INLINE void fill (const Scalar v)

EIGEN_STRONG_INLINE void assign (const Scalar v)

EIGEN_STRONG_INLINE void assign (size_t N, const Scalar v)

EIGEN_STRONG_INLINE size_t getRowCount () const

Get number of rows.

EIGEN_STRONG_INLINE size_t getColCount () const

Get number of columns.

EIGEN_STRONG_INLINE void unit (const size_t nRows, const Scalar diag_vals)

Make the matrix an identity matrix (the diagonal values can be 1.0 or any other value)

EIGEN_STRONG_INLINE void unit ()

Make the matrix an identity matrix.

EIGEN_STRONG_INLINE void eye ()

Make the matrix an identity matrix.

EIGEN_STRONG_INLINE void zeros ()

Set all elements to zero.

EIGEN_STRONG_INLINE void zeros (const size_t row, const size_t col)

Resize and set all elements to zero.

EIGEN_STRONG_INLINE void ones (const size_t row, const size_t col)

Resize matrix and set all elements to one.

EIGEN_STRONG_INLINE void ones ()

Set all elements to one.

EIGEN_STRONG_INLINE Scalar * get_unsafe_row (size_t row)

Fast but unsafe method to obtain a pointer to a given row of the matrix (Use only in time critical applications) VERY IMPORTANT WARNING: You must be aware of the memory layout, either Column or Row-major ordering.

EIGEN_STRONG_INLINE const Scalar * get_unsafe_row (size_t row) const

EIGEN_STRONG_INLINE Scalar get_unsafe (const size_t row, const size_t col) const

Read-only access to one element (Use with caution, bounds are not checked!)

EIGEN_STRONG_INLINE Scalar & get_unsafe (const size_t row, const size_t col)

Reference access to one element (Use with caution, bounds are not checked!)

EIGEN_STRONG_INLINE void set_unsafe (const size_t row, const size_t col, const Scalar val)

Sets an element (Use with caution, bounds are not checked!)

EIGEN_STRONG_INLINE void push_back (Scalar val)

Insert an element at the end of the container (for 1D vectors/arrays)

EIGEN_STRONG_INLINE bool isSquare () const

EIGEN_STRONG_INLINE bool isSingular (const Scalar absThreshold=0) const

bool fromMatlabStringFormat (const std::string &s, bool dumpErrorMsgToStdErr=true)

Read a matrix from a string in Matlab-like format, for example "[1 0 2; 0 4 -1]" The string must start with '[' and end with ']'.

std::string inMatlabFormat (const size_t decimal_digits=6) const

Dump matrix in matlab format.

void saveToTextFile (const std::string &file, mrpt::math::TMatrixTextFileFormat fileFormat=mrpt::math::MATRIX_FORMAT_ENG, bool appendMRPTHeader=false, const std::string &userHeader=std::string()) const

Save matrix to a text file, compatible with MATLAB text format (see also the methods of matrix classes themselves).

void loadFromTextFile (const std::string &file)

Load matrix from a text file, compatible with MATLAB text format.

void loadFromTextFile (std::istream &_input_text_stream)

EIGEN_STRONG_INLINE void multiplyColumnByScalar (size_t c, Scalar s)

EIGEN_STRONG_INLINE void multiplyRowByScalar (size_t r, Scalar s)

EIGEN_STRONG_INLINE void swapCols (size_t i1, size_t i2)

EIGEN_STRONG_INLINE void swapRows (size_t i1, size_t i2)

EIGEN_STRONG_INLINE size_t countNonZero () const

EIGEN_STRONG_INLINE Scalar maximum () const

[VECTORS OR MATRICES] Finds the maximum value

Exceptions:

std::exception On an empty input container

EIGEN_STRONG_INLINE Scalar maximum (size_t *maxIndex) const

[VECTORS ONLY] Finds the maximum value (and the corresponding zero-based index) from a given container.

EIGEN_STRONG_INLINE Scalar minimum () const

[VECTORS OR MATRICES] Finds the minimum value

EIGEN_STRONG_INLINE Scalar minimum (size_t *minIndex) const

[VECTORS ONLY] Finds the minimum value (and the corresponding zero-based index) from a given container.

EIGEN_STRONG_INLINE void minimum_maximum (Scalar &out_min, Scalar &out_max) const

[VECTORS OR MATRICES] Compute the minimum and maximum of a container at once

EIGEN_STRONG_INLINE void minimum_maximum (Scalar &out_min, Scalar &out_max, size_t *minIndex, size_t *maxIndex) const

[VECTORS ONLY] Compute the minimum and maximum of a container at once

void find_index_max_value (size_t &u, size_t &v, Scalar &valMax) const

[VECTORS OR MATRICES] Finds the maximum value (and the corresponding zero-based index) from a given container.

EIGEN_STRONG_INLINE Scalar norm_inf () const

Compute the norm-infinite of a vector ($f[ ||{v}||_ $f]), ie the maximum absolute value of the elements.

EIGEN_STRONG_INLINE Scalar squareNorm () const

Compute the square norm of a vector/array/matrix (the Euclidean distance to the origin, taking all the elements as a single vector).

EIGEN_STRONG_INLINE Scalar sumAll () const

EIGEN_STRONG_INLINE void laplacian (Eigen::MatrixBase< OtherDerived > &ret) const

Computes the laplacian of this square graph weight matrix.

EIGEN_STRONG_INLINE void setSize (size_t row, size_t col)

Changes the size of matrix, maintaining its previous content as possible and padding with zeros where applicable.

void largestEigenvector (OUTVECT &x, Scalar resolution=Scalar(0.01), size_t maxIterations=6, int *out_Iterations=NULL, float *out_estimatedResolution=NULL) const

Efficiently computes only the biggest eigenvector of the matrix using the Power Method, and returns it in the passed vector "x".

MatrixBase< Derived > & operator^= (const unsigned int pow)

Combined matrix power and assignment operator.

EIGEN_STRONG_INLINE void scalarPow (const Scalar s)

Scalar power of all elements to a given power, this is diferent of ^ operator.

EIGEN_STRONG_INLINE bool isDiagonal () const

Checks for matrix type.

EIGEN_STRONG_INLINE Scalar maximumDiagonal () const

Finds the maximum value in the diagonal of the matrix.

EIGEN_STRONG_INLINE double mean () const

Computes the mean of the entire matrix.

void meanAndStd (VEC &outMeanVector, VEC &outStdVector, const bool unbiased_variance=true) const

Computes a row with the mean values of each column in the matrix and the associated vector with the standard deviation of each column.

void meanAndStdAll (double &outMean, double &outStd, const bool unbiased_variance=true) const

Computes the mean and standard deviation of all the elements in the matrix as a whole.

EIGEN_STRONG_INLINE void insertMatrix (size_t r, size_t c, const MAT &m)

Insert matrix "m" into this matrix at indices (r,c), that is, (*this)(r,c)=m(0,0) and so on.

EIGEN_STRONG_INLINE void insertMatrixTranspose (size_t r, size_t c, const MAT &m)

EIGEN_STRONG_INLINE void insertRow (size_t nRow, const MAT &aRow)

void insertRow (size_t nRow, const std::vector< R > &aRow)

EIGEN_STRONG_INLINE void insertCol (size_t nCol, const MAT &aCol)

void insertCol (size_t nCol, const std::vector< R > &aCol)

EIGEN_STRONG_INLINE void removeColumns (const std::vector< size_t > &idxsToRemove)

Remove columns of the matrix.

EIGEN_STRONG_INLINE void unsafeRemoveColumns (const std::vector< size_t > &idxs)

Remove columns of the matrix.

EIGEN_STRONG_INLINE void removeRows (const std::vector< size_t > &idxsToRemove)

Remove rows of the matrix.

EIGEN_STRONG_INLINE void unsafeRemoveRows (const std::vector< size_t > &idxs)

Remove rows of the matrix.

EIGEN_STRONG_INLINE const
AdjointReturnType t () const

Transpose.

EIGEN_STRONG_INLINE PlainObject inv () const

EIGEN_STRONG_INLINE void inv (MATRIX &outMat) const

EIGEN_STRONG_INLINE void inv_fast (MATRIX &outMat) const

EIGEN_STRONG_INLINE Scalar det () const

MRPT plugin: Multiply and extra addition functions

EIGEN_STRONG_INLINE bool empty () const

EIGEN_STRONG_INLINE void add_Ac (const OTHERMATRIX &m, const Scalar c)

EIGEN_STRONG_INLINE void substract_Ac (const OTHERMATRIX &m, const Scalar c)

EIGEN_STRONG_INLINE void substract_At (const OTHERMATRIX &m)

EIGEN_STRONG_INLINE void substract_An (const OTHERMATRIX &m, const size_t n)

EIGEN_STRONG_INLINE void add_AAt (const OTHERMATRIX &A)

EIGEN_STRONG_INLINE void substract_AAt (const OTHERMATRIX &A)

EIGEN_STRONG_INLINE void multiply (const MATRIX1 &A, const MATRIX2 &B)

EIGEN_STRONG_INLINE void multiply_AB (const MATRIX1 &A, const MATRIX2 &B)

EIGEN_STRONG_INLINE void multiply_AtB (const MATRIX1 &A, const MATRIX2 &B)

EIGEN_STRONG_INLINE void multiply_Ab (const OTHERVECTOR1 &vIn, OTHERVECTOR2 &vOut, bool accumToOutput=false) const

EIGEN_STRONG_INLINE void multiply_Atb (const OTHERVECTOR1 &vIn, OTHERVECTOR2 &vOut, bool accumToOutput=false) const

EIGEN_STRONG_INLINE void multiply_HCHt (const MAT_C &C, MAT_R &R, bool accumResultInOutput=false) const

EIGEN_STRONG_INLINE void multiply_HtCH (const MAT_C &C, MAT_R &R, bool accumResultInOutput=false) const

EIGEN_STRONG_INLINE Scalar multiply_HCHt_scalar (const MAT_C &C) const

EIGEN_STRONG_INLINE Scalar multiply_HtCH_scalar (const MAT_C &C) const

EIGEN_STRONG_INLINE void multiply_AAt_scalar (const MAT_A &A, typename MAT_A::value_type f)

EIGEN_STRONG_INLINE void multiply_AtA_scalar (const MAT_A &A, typename MAT_A::value_type f)

void multiply_A_skew3 (const MAT_A &A, const SKEW_3VECTOR &v)

void multiply_skew3_A (const SKEW_3VECTOR &v, const MAT_A &A)

EIGEN_STRONG_INLINE void multiply_subMatrix (const MAT_A &A, MAT_OUT &outResult, const size_t A_cols_offset, const size_t A_rows_offset, const size_t A_col_count) const

outResult = this * A

void multiply_ABC (const MAT_A &A, const MAT_B &B, const MAT_C &C)

void multiply_ABCt (const MAT_A &A, const MAT_B &B, const MAT_C &C)

void multiply_AtBC (const MAT_A &A, const MAT_B &B, const MAT_C &C)

EIGEN_STRONG_INLINE void multiply_ABt (const MAT_A &A, const MAT_B &B)

EIGEN_STRONG_INLINE void multiply_AAt (const MAT_A &A)

EIGEN_STRONG_INLINE void multiply_AtA (const MAT_A &A)

EIGEN_STRONG_INLINE void multiply_result_is_symmetric (const MAT_A &A, const MAT_B &B)

EIGEN_STRONG_INLINE void leftDivideSquare (const MAT2 &A, MAT3 &RES) const

Matrix left divide: RES = A^-1 * this , with A being squared (using the Eigen::ColPivHouseholderQR method)

EIGEN_STRONG_INLINE void rightDivideSquare (const MAT2 &B, MAT3 &RES) const

Matrix right divide: RES = this * B^-1, with B being squared (using the Eigen::ColPivHouseholderQR method)

MRPT plugin: Eigenvalue / Eigenvectors

EIGEN_STRONG_INLINE void eigenVectors (MATRIX1 &eVecs, MATRIX2 &eVals) const

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), both returned as matrices: eigenvectors are the columns in "eVecs", and eigenvalues in ascending order as the diagonal of "eVals".

EIGEN_STRONG_INLINE void eigenVectorsVec (MATRIX1 &eVecs, VECTOR1 &eVals) const

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), eigenvectors are the columns in "eVecs", and eigenvalues are returned in in ascending order in the vector "eVals".

EIGEN_STRONG_INLINE void eigenValues (VECTOR &eVals) const

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), and return only the eigenvalues in the vector "eVals".

EIGEN_STRONG_INLINE void eigenVectorsSymmetric (MATRIX1 &eVecs, MATRIX2 &eVals) const

[For symmetric matrices only] Compute the eigenvectors and eigenvalues (in no particular order), both returned as matrices: eigenvectors are the columns, and eigenvalues

EIGEN_STRONG_INLINE void eigenVectorsSymmetricVec (MATRIX1 &eVecs, VECTOR1 &eVals) const

[For symmetric matrices only] Compute the eigenvectors and eigenvalues (in no particular order), both returned as matrices: eigenvectors are the columns, and eigenvalues

MRPT plugin: Linear algebra & decomposition-based methods

EIGEN_STRONG_INLINE bool chol (MATRIX &U) const

Cholesky M=U^T * U decomposition for simetric matrix (upper-half of the matrix will be actually ignored)

EIGEN_STRONG_INLINE size_t rank (double threshold=0) const

Gets the rank of the matrix via the Eigen::ColPivHouseholderQR method.

MRPT plugin: Scalar and element-wise extra operators

EIGEN_STRONG_INLINE MatrixBase
< Derived > & Sqrt ()

EIGEN_STRONG_INLINE PlainObject Sqrt () const

EIGEN_STRONG_INLINE MatrixBase
< Derived > & Abs ()

EIGEN_STRONG_INLINE PlainObject Abs () const

EIGEN_STRONG_INLINE MatrixBase
< Derived > & Log ()

EIGEN_STRONG_INLINE PlainObject Log () const

EIGEN_STRONG_INLINE MatrixBase
< Derived > & Exp ()

EIGEN_STRONG_INLINE PlainObject Exp () const

EIGEN_STRONG_INLINE MatrixBase
< Derived > & Square ()

EIGEN_STRONG_INLINE PlainObject Square () const

void normalize (Scalar valMin, Scalar valMax)

Scales all elements such as the minimum & maximum values are shifted to the given values.

void adjustRange (Scalar valMin, Scalar valMax)

Static Public Member Functions

static const IdentityReturnType Identity ()

static const IdentityReturnType Identity (Index rows, Index cols)

static const BasisReturnType Unit (Index size, Index i)

static const BasisReturnType Unit (Index i)

static const BasisReturnType UnitX ()

static const BasisReturnType UnitY ()

static const BasisReturnType UnitZ ()

static const BasisReturnType UnitW ()

Protected Member Functions

Derived & operator+= (const ArrayBase< OtherDerived > &)

Derived & operator-= (const ArrayBase< OtherDerived > &)

Protected Attributes

const LhsNested m_lhs

const RhsNested m_rhs

PlainObject

m_result

Private Types

enum { PacketSize = internal::packet_traits<Scalar>::size, InnerSize = internal::traits<CoeffBasedProduct>::InnerSize, Unroll = CoeffReadCost != Dynamic && CoeffReadCost <= EIGEN_UNROLLING_LIMIT, CanVectorizeInner = internal::traits<CoeffBasedProduct>::CanVectorizeInner }

typedef internal::traits
< CoeffBasedProduct >
::_LhsNested _LhsNested

typedef internal::traits
< CoeffBasedProduct >
::_RhsNested _RhsNested

typedef
internal::product_coeff_impl
< CanVectorizeInner?InnerVectorizedTraversal:DefaultTraversal,
Unroll?InnerSize-1:Dynamic,
_LhsNested, _RhsNested, Scalar > ScalarCoeffImpl

typedef CoeffBasedProduct
< LhsNested, RhsNested,
NestByRefBit > LazyCoeffBasedProductType

Friends

const ScalarMultipleReturnType operator* (const Scalar &scalar, const StorageBaseType &matrix)

const CwiseUnaryOp
< internal::scalar_multiple2_op
< Scalar, std::complex< Scalar >
>, const Derived > operator* (const std::complex< Scalar > &scalar, const StorageBaseType &matrix)

MRPT plugin: Basic iterators. These iterators are intended for 1D matrices only, i.e. column or row vectors.

typedef Scalar * iterator

typedef const Scalar * const_iterator

EIGEN_STRONG_INLINE iterator begin ()

EIGEN_STRONG_INLINE const_iterator begin () const

EIGEN_STRONG_INLINE iterator end ()

EIGEN_STRONG_INLINE const_iterator end () const

Member Typedef Documentation

typedef internal::traits<CoeffBasedProduct>::_LhsNested Eigen::CoeffBasedProduct::_LhsNested [private]

Definition at line 139 of file Core.

typedef internal::traits<CoeffBasedProduct>::_RhsNested Eigen::CoeffBasedProduct::_RhsNested [private]

Definition at line 140 of file Core.

typedef MatrixBase<CoeffBasedProduct> Eigen::CoeffBasedProduct::Base

Definition at line 133 of file Core.

typedef const Scalar* Eigen::MatrixBase::const_iterator [inherited]

Definition at line 45 of file Core.

typedef const Diagonal<const Derived> Eigen::MatrixBase::ConstDiagonalReturnType [inherited]

Definition at line 228 of file Core.

typedef Block<const Derived, internal::traits<Derived>::ColsAtCompileTime==1 ? SizeMinusOne : 1, internal::traits<Derived>::ColsAtCompileTime==1 ? 1 : SizeMinusOne> Eigen::MatrixBase::ConstStartMinusOne [inherited]

Definition at line 431 of file Core.

typedef Diagonal<Derived> Eigen::MatrixBase::DiagonalReturnType [inherited]

Definition at line 226 of file Core.

typedef CwiseUnaryOp<internal::scalar_quotient1_op<typename internal::traits<Derived>::Scalar>, const ConstStartMinusOne > Eigen::MatrixBase::HNormalizedReturnType [inherited]

Definition at line 433 of file Core.

typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> Eigen::MatrixBase::HomogeneousReturnType [inherited]

Definition at line 422 of file Core.

typedef Scalar* Eigen::MatrixBase::iterator [inherited]

Definition at line 44 of file Core.

typedef CoeffBasedProduct<LhsNested,RhsNested,NestByRefBit> Eigen::CoeffBasedProduct::LazyCoeffBasedProductType [private]

Definition at line 153 of file Core.

typedef Base::PlainObject Eigen::CoeffBasedProduct::PlainObject

The plain matrix type corresponding to this expression.

This is not necessarily exactly the return type of eval(). In the case of plain matrices, the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either PlainObject or const PlainObject&.

Reimplemented from Eigen::MatrixBase< CoeffBasedProduct< LhsNested, RhsNested, NestingFlags > >.

Definition at line 135 of file Core.

typedef internal::product_coeff_impl<CanVectorizeInner ? InnerVectorizedTraversal : DefaultTraversal, Unroll ? InnerSize-1 : Dynamic, _LhsNested, _RhsNested, Scalar> Eigen::CoeffBasedProduct::ScalarCoeffImpl [private]

Definition at line 151 of file Core.

typedef internal::stem_function<Scalar>::type Eigen::MatrixBase::StemFunction [inherited]

Definition at line 461 of file Core.

typedef Scalar Eigen::MatrixBase::value_type [inherited]

Type of the elements.

Definition at line 36 of file Core.

Member Enumeration Documentation

anonymous enum [inherited]

Definition at line 38 of file Core.

anonymous enum [inherited]

Definition at line 421 of file Core.

anonymous enum [inherited]

Definition at line 426 of file Core.

anonymous enum [private]

Enumerator:

PacketSize
InnerSize
Unroll
CanVectorizeInner

Definition at line 142 of file Core.

Constructor & Destructor Documentation

Eigen::CoeffBasedProduct::CoeffBasedProduct ( const CoeffBasedProduct & other ) [inline]

Definition at line 157 of file Core.

template<typename Lhs , typename Rhs >

Eigen::CoeffBasedProduct::CoeffBasedProduct	(	const Lhs &	lhs,
		const Rhs &	rhs
	)		`[inline]`

Definition at line 162 of file Core.

Member Function Documentation

EIGEN_STRONG_INLINE MatrixBase<Derived>& Eigen::MatrixBase::Abs ( ) [inline, inherited]

Definition at line 740 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::Abs ( ) const [inline, inherited]

Definition at line 741 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::add_AAt ( const OTHERMATRIX & A ) [inline, inherited]

this += A + A^T

Definition at line 518 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::add_Ac	(	const OTHERMATRIX &	m,
		const Scalar	c
	)		`[inline, inherited]`

Add c (scalar) times A to this matrix: this += A * c

Definition at line 507 of file Core.

const AdjointReturnType Eigen::MatrixBase::adjoint ( ) const [inherited]

Returns:: an expression of the adjoint (i.e. conjugate transpose) of *this.

Example:

Output:

Warning:

If you want to replace a matrix by its own adjoint, do NOT do this:

 m = m.adjoint(); // bug!!! caused by aliasing effect

Instead, use the adjointInPlace() method:

 m.adjointInPlace();

which gives Eigen good opportunities for optimization, or alternatively you can also do:

 m = m.adjoint().eval();

See also:: adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op

void Eigen::MatrixBase::adjointInPlace ( ) [inherited]

This is the "in place" version of adjoint(): it replaces *this by its own transpose.

Thus, doing

 m.adjointInPlace();

has the same effect on m as doing

 m = m.adjoint().eval();

and is faster and also safer because in the latter line of code, forgetting the eval() results in a bug caused by aliasing.

Notice however that this method is only useful if you want to replace a matrix by its own adjoint. If you just need the adjoint of a matrix, use adjoint().

Note:: if the matrix is not square, then *this must be a resizable matrix.

See also:: transpose(), adjoint(), transposeInPlace()

void Eigen::MatrixBase::adjustRange	(	Scalar	valMin,
		Scalar	valMax
	)		`[inline, inherited]`

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Definition at line 764 of file Core.

void Eigen::MatrixBase::applyHouseholderOnTheLeft	(	const EssentialPart &	essential,
		const Scalar &	tau,
		Scalar *	workspace
	)		`[inherited]`

void Eigen::MatrixBase::applyHouseholderOnTheRight	(	const EssentialPart &	essential,
		const Scalar &	tau,
		Scalar *	workspace
	)		`[inherited]`

void Eigen::MatrixBase::applyOnTheLeft ( const EigenBase< OtherDerived > & other ) [inherited]

replaces *this by *this * other.

void Eigen::MatrixBase::applyOnTheLeft	(	Index	p,
		Index	q,
		const JacobiRotation< OtherScalar > &	j
	)		`[inherited]`

Applies the rotation in the plane j to the rows p and q of *this, i.e., it computes B = J * B, with $B = \left ( \begin{array}{cc} \text{*this.row}(p) \\ \text{*this.row}(q) \end{array} \right )$ .

See also:: class JacobiRotation, MatrixBase::applyOnTheRight(), internal::apply_rotation_in_the_plane()

void Eigen::MatrixBase::applyOnTheRight ( const EigenBase< OtherDerived > & other ) [inherited]

replaces *this by *this * other.

It is equivalent to MatrixBase::operator*=()

void Eigen::MatrixBase::applyOnTheRight	(	Index	p,
		Index	q,
		const JacobiRotation< OtherScalar > &	j
	)		`[inherited]`

Applies the rotation in the plane j to the columns p and q of *this, i.e., it computes B = B * J with $B = \left ( \begin{array}{cc} \text{*this.col}(p) & \text{*this.col}(q) \end{array} \right )$ .

See also:: class JacobiRotation, MatrixBase::applyOnTheLeft(), internal::apply_rotation_in_the_plane()

ArrayWrapper<Derived> Eigen::MatrixBase::array ( ) [inline, inherited]

Returns:: an Array expression of this matrix

See also:: ArrayBase::matrix()

Definition at line 332 of file Core.

const ArrayWrapper<Derived> Eigen::MatrixBase::array ( ) const [inline, inherited]

Definition at line 333 of file Core.

const DiagonalWrapper<const Derived> Eigen::MatrixBase::asDiagonal ( ) const [inherited]

Returns:: a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients

Example:

Output:

See also:: class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()

const PermutationWrapper<const Derived> Eigen::MatrixBase::asPermutation ( ) const [inherited]

EIGEN_STRONG_INLINE void Eigen::MatrixBase::assign ( const Scalar v ) [inline, inherited]

Fill all the elements with a given value

Definition at line 62 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::assign	(	size_t	N,
		const Scalar	v
	)		`[inline, inherited]`

Resize to N and set all the elements to a given value

Definition at line 64 of file Core.

EIGEN_STRONG_INLINE iterator Eigen::MatrixBase::begin ( ) [inline, inherited]

Definition at line 47 of file Core.

EIGEN_STRONG_INLINE const_iterator Eigen::MatrixBase::begin ( ) const [inline, inherited]

Definition at line 49 of file Core.

EIGEN_STRONG_INLINE const CwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived> Eigen::MatrixBase::binaryExpr	(	const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > &	other,
		const CustomBinaryOp &	func = `CustomBinaryOp()`
	)		const `[inline, inherited]`

Returns:: an expression of the difference of *this and other

Note:: If you want to substract a given scalar from all coefficients, see Cwise::operator-().

See also:: class CwiseBinaryOp, operator-=()

Returns:: an expression of the sum of *this and other

Note:: If you want to add a given scalar to all coefficients, see Cwise::operator+().

See also:: class CwiseBinaryOp, operator+=()

Returns:: an expression of a custom coefficient-wise operator func of *this and other

The template parameter CustomBinaryOp is the type of the functor of the custom operator (see class CwiseBinaryOp for an example)

Here is an example illustrating the use of custom functors:

Output:

See also:: class CwiseBinaryOp, operator+(), operator-(), cwiseProduct()

Definition at line 58 of file Core.

RealScalar Eigen::MatrixBase::blueNorm ( ) const [inherited]

Returns:: the l2 norm of *this using the Blue's algorithm. A Portable Fortran Program to Find the Euclidean Norm of a Vector, ACM TOMS, Vol 4, Issue 1, 1978.

For architecture/scalar types without vectorization, this version is much faster than stableNorm(). Otherwise the stableNorm() is faster.

See also:: norm(), stableNorm(), hypotNorm()

internal::cast_return_type<Derived,const CwiseUnaryOp<internal::scalar_cast_op<typename internal::traits<Derived>::Scalar, NewType>, const Derived> >::type Eigen::MatrixBase::cast ( ) const [inline, inherited]

Returns:: an expression of *this with the Scalar type casted to NewScalar.

The template parameter NewScalar is the type we are casting the scalars to.

See also:: class CwiseUnaryOp

Definition at line 108 of file Core.

EIGEN_STRONG_INLINE bool Eigen::MatrixBase::chol ( MATRIX & U ) const [inline, inherited]

Cholesky M=U^T * U decomposition for simetric matrix (upper-half of the matrix will be actually ignored)

Definition at line 711 of file Core.

EIGEN_STRONG_INLINE const Scalar Eigen::CoeffBasedProduct::coeff	(	Index	row,
		Index	col
	)		const `[inline]`

Definition at line 177 of file Core.

EIGEN_STRONG_INLINE const Scalar Eigen::CoeffBasedProduct::coeff ( Index index ) const [inline]

Definition at line 187 of file Core.

const ColPivHouseholderQR<PlainObject> Eigen::MatrixBase::colPivHouseholderQr ( ) const [inherited]

Returns:: the column-pivoting Householder QR decomposition of *this.

See also:: class ColPivHouseholderQR

EIGEN_STRONG_INLINE Index Eigen::CoeffBasedProduct::cols ( void ) const [inline]

Definition at line 175 of file Core.

void Eigen::MatrixBase::computeInverseAndDetWithCheck	(	ResultType &	inverse,
		typename ResultType::Scalar &	determinant,
		bool &	invertible,
		const RealScalar &	absDeterminantThreshold = `NumTraits<Scalar>::dummy_precision()`
	)		const `[inherited]`

Computation of matrix inverse and determinant, with invertibility check.

This is only for fixed-size square matrices of size up to 4x4.

Parameters:

inverse	Reference to the matrix in which to store the inverse.
determinant	Reference to the variable in which to store the inverse.
invertible	Reference to the bool variable in which to store whether the matrix is invertible.
absDeterminantThreshold	Optional parameter controlling the invertibility check. The matrix will be declared invertible if the absolute value of its determinant is greater than this threshold.

Example:

Output:

See also:: inverse(), computeInverseWithCheck()

void Eigen::MatrixBase::computeInverseWithCheck	(	ResultType &	inverse,
		bool &	invertible,
		const RealScalar &	absDeterminantThreshold = `NumTraits<Scalar>::dummy_precision()`
	)		const `[inherited]`

Computation of matrix inverse, with invertibility check.

This is only for fixed-size square matrices of size up to 4x4.

Parameters:

inverse	Reference to the matrix in which to store the inverse.
invertible	Reference to the bool variable in which to store whether the matrix is invertible.
absDeterminantThreshold	Optional parameter controlling the invertibility check. The matrix will be declared invertible if the absolute value of its determinant is greater than this threshold.

Example:

Output:

See also:: inverse(), computeInverseAndDetWithCheck()

ConjugateReturnType Eigen::MatrixBase::conjugate ( ) const [inline, inherited]

Returns:: an expression of the complex conjugate of *this.

See also:: adjoint()

Definition at line 117 of file Core.

const MatrixFunctionReturnValue<Derived> Eigen::MatrixBase::cos ( ) const [inherited]

const MatrixFunctionReturnValue<Derived> Eigen::MatrixBase::cosh ( ) const [inherited]

EIGEN_STRONG_INLINE size_t Eigen::MatrixBase::countNonZero ( ) const [inline, inherited]

Definition at line 190 of file Core.

cross_product_return_type<OtherDerived>::type Eigen::MatrixBase::cross ( const MatrixBase< OtherDerived > & other ) const [inherited]

Returns:: the cross product of *this and other

Here is a very good explanation of cross-product: http://xkcd.com/199/

See also:: MatrixBase::cross3()

PlainObject Eigen::MatrixBase::cross3 ( const MatrixBase< OtherDerived > & other ) const [inherited]

Returns:: the cross product of *this and other using only the x, y, and z coefficients

The size of *this and other must be four. This function is especially useful when using 4D vectors instead of 3D ones to get advantage of SSE/AltiVec vectorization.

See also:: MatrixBase::cross()

EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived> Eigen::MatrixBase::cwiseAbs ( ) const [inline, inherited]

Returns:: an expression of the coefficient-wise absolute value of *this

Example:

Output:

See also:: cwiseAbs2()

Definition at line 37 of file Core.

EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const Derived> Eigen::MatrixBase::cwiseAbs2 ( ) const [inline, inherited]

Returns:: an expression of the coefficient-wise squared absolute value of *this

Example:

Output:

See also:: cwiseAbs()

Definition at line 47 of file Core.

const CwiseBinaryOp<std::equal_to<Scalar>, const Derived, const OtherDerived> Eigen::MatrixBase::cwiseEqual ( const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > & other ) const [inline, inherited]

Returns:: an expression of the coefficient-wise == operator of *this and other

Warning:: this performs an exact comparison, which is generally a bad idea with floating-point types. In order to check for equality between two vectors or matrices with floating-point coefficients, it is generally a far better idea to use a fuzzy comparison as provided by isApprox() and isMuchSmallerThan().

Example:

Output:

See also:: cwiseNotEqual(), isApprox(), isMuchSmallerThan()

Definition at line 57 of file Core.

const CwiseUnaryOp<std::binder1st<std::equal_to<Scalar> >, const Derived> Eigen::MatrixBase::cwiseEqual ( const Scalar & s ) const [inline, inherited]

Returns:: an expression of the coefficient-wise == operator of *this and a scalar s

Warning:: this performs an exact comparison, which is generally a bad idea with floating-point types. In order to check for equality between two vectors or matrices with floating-point coefficients, it is generally a far better idea to use a fuzzy comparison as provided by isApprox() and isMuchSmallerThan().

See also:: cwiseEqual(const MatrixBase<OtherDerived> &) const

Definition at line 79 of file Core.

const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived> Eigen::MatrixBase::cwiseInverse ( ) const [inline, inherited]

Returns:: an expression of the coefficient-wise inverse of *this.

Example:

Output:

See also:: cwiseProduct()

Definition at line 67 of file Core.

EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived> Eigen::MatrixBase::cwiseMax ( const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > & other ) const [inline, inherited]

Returns:: an expression of the coefficient-wise max of *this and other

Example:

Output:

See also:: class CwiseBinaryOp, min()

Definition at line 104 of file Core.

EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived> Eigen::MatrixBase::cwiseMin ( const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > & other ) const [inline, inherited]

Returns:: an expression of the coefficient-wise min of *this and other

Example:

Output:

See also:: class CwiseBinaryOp, max()

Definition at line 90 of file Core.

const CwiseBinaryOp<std::not_equal_to<Scalar>, const Derived, const OtherDerived> Eigen::MatrixBase::cwiseNotEqual ( const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > & other ) const [inline, inherited]

Returns:: an expression of the coefficient-wise != operator of *this and other

Warning:: this performs an exact comparison, which is generally a bad idea with floating-point types. In order to check for equality between two vectors or matrices with floating-point coefficients, it is generally a far better idea to use a fuzzy comparison as provided by isApprox() and isMuchSmallerThan().

Example:

Output:

See also:: cwiseEqual(), isApprox(), isMuchSmallerThan()

Definition at line 76 of file Core.

EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived> Eigen::MatrixBase::cwiseQuotient ( const EIGEN_CURRENT_STORAGE_BASE_CLASS< OtherDerived > & other ) const [inline, inherited]

Returns:: an expression of the coefficient-wise quotient of *this and other

Example:

Output:

See also:: class CwiseBinaryOp, cwiseProduct(), cwiseInverse()

Definition at line 118 of file Core.

const CwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived> Eigen::MatrixBase::cwiseSqrt ( ) const [inline, inherited]

Returns:: an expression of the coefficient-wise square root of *this.

Example:

Output:

See also:: cwisePow(), cwiseSquare()

Definition at line 57 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::det ( ) const [inline, inherited]

Definition at line 496 of file Core.

Scalar Eigen::MatrixBase::determinant ( ) const [inherited]

Returns:: the determinant of this matrix

const Diagonal<const LazyCoeffBasedProductType,0> Eigen::CoeffBasedProduct::diagonal ( ) const [inline]

Reimplemented from Eigen::MatrixBase< CoeffBasedProduct< LhsNested, RhsNested, NestingFlags > >.

Definition at line 217 of file Core.

template<int DiagonalIndex>

const Diagonal<const LazyCoeffBasedProductType,DiagonalIndex> Eigen::CoeffBasedProduct::diagonal ( ) const [inline]

Reimplemented from Eigen::MatrixBase< CoeffBasedProduct< LhsNested, RhsNested, NestingFlags > >.

Definition at line 221 of file Core.

const Diagonal<const LazyCoeffBasedProductType,Dynamic> Eigen::CoeffBasedProduct::diagonal ( Index index ) const [inline]

Reimplemented from Eigen::MatrixBase< CoeffBasedProduct< LhsNested, RhsNested, NestingFlags > >.

Definition at line 224 of file Core.

DiagonalReturnType Eigen::MatrixBase::diagonal ( ) [inherited]

Returns:: an expression of the main diagonal of the matrix *this

*this is not required to be square.

Example:

Output:

See also:: class Diagonal

Returns:: an expression of the DiagIndex-th sub or super diagonal of the matrix *this

*this is not required to be square.

The template parameter DiagIndex represent a super diagonal if DiagIndex > 0 and a sub diagonal otherwise. DiagIndex == 0 is equivalent to the main diagonal.

Example:

Output:

See also:: MatrixBase::diagonal(), class Diagonal

DiagonalIndexReturnType<Dynamic>::Type Eigen::MatrixBase::diagonal ( Index index ) [inherited]

Returns:: an expression of the DiagIndex-th sub or super diagonal of the matrix *this

*this is not required to be square.

The template parameter DiagIndex represent a super diagonal if DiagIndex > 0 and a sub diagonal otherwise. DiagIndex == 0 is equivalent to the main diagonal.

Example:

Output:

See also:: MatrixBase::diagonal(), class Diagonal

Index Eigen::MatrixBase::diagonalSize ( ) const [inline, inherited]

Returns:: the size of the main diagonal, which is min(rows(),cols()).

See also:: rows(), cols(), SizeAtCompileTime.

Definition at line 115 of file Core.

internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase::dot ( const MatrixBase< OtherDerived > & other ) const [inherited]

Returns:: the dot product of *this with other.

Note:: If the scalar type is complex numbers, then this function returns the hermitian (sesquilinear) dot product, conjugate-linear in the first variable and linear in the second variable.

See also:: squaredNorm(), norm()

EIGEN_STRONG_INLINE const Eigen::MatrixBase::EIGEN_CWISE_PRODUCT_RETURN_TYPE	(	Derived	,
		OtherDerived
	)		const `[inline, inherited]`

Returns:: an expression of the Schur product (coefficient wise product) of *this and other

Example:

Output:

See also:: class CwiseBinaryOp, cwiseAbs2

Definition at line 37 of file Core.

EigenvaluesReturnType Eigen::MatrixBase::eigenvalues ( ) const [inherited]

Computes the eigenvalues of a matrix.

Returns:: Column vector containing the eigenvalues.

This function computes the eigenvalues with the help of the EigenSolver class (for real matrices) or the ComplexEigenSolver class (for complex matrices).

The eigenvalues are repeated according to their algebraic multiplicity, so there are as many eigenvalues as rows in the matrix.

The SelfAdjointView class provides a better algorithm for selfadjoint matrices.

Example:

Output:

See also:: EigenSolver::eigenvalues(), ComplexEigenSolver::eigenvalues(), SelfAdjointView::eigenvalues()

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eigenValues ( VECTOR & eVals ) const [inline, inherited]

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), and return only the eigenvalues in the vector "eVals".

Note:: Warning: Only the real part of complex eigenvectors and eigenvalues are returned.

See also:: eigenVectorsSymmetric, eigenVectorsVec

Definition at line 683 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eigenVectors	(	MATRIX1 &	eVecs,
		MATRIX2 &	eVals
	)		const `[inherited]`

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), both returned as matrices: eigenvectors are the columns in "eVecs", and eigenvalues in ascending order as the diagonal of "eVals".

Compute the eigenvectors and eigenvalues, both returned as matrices: eigenvectors are the columns, and eigenvalues.

Note:: Warning: Only the real part of complex eigenvectors and eigenvalues are returned.

See also:: eigenVectorsSymmetric, eigenVectorsVec

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eigenVectorsSymmetric	(	MATRIX1 &	eVecs,
		MATRIX2 &	eVals
	)		const `[inherited]`

[For symmetric matrices only] Compute the eigenvectors and eigenvalues (in no particular order), both returned as matrices: eigenvectors are the columns, and eigenvalues

Compute the eigenvectors and eigenvalues, both returned as matrices: eigenvectors are the columns, and eigenvalues.

See also:: eigenVectors

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eigenVectorsSymmetricVec	(	MATRIX1 &	eVecs,
		VECTOR1 &	eVals
	)		const `[inherited]`

[For symmetric matrices only] Compute the eigenvectors and eigenvalues (in no particular order), both returned as matrices: eigenvectors are the columns, and eigenvalues

Compute the eigenvectors and eigenvalues, both returned as matrices: eigenvectors are the columns, and eigenvalues.

See also:: eigenVectorsVec

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eigenVectorsVec	(	MATRIX1 &	eVecs,
		VECTOR1 &	eVals
	)		const `[inherited]`

[For square matrices only] Compute the eigenvectors and eigenvalues (sorted), eigenvectors are the columns in "eVecs", and eigenvalues are returned in in ascending order in the vector "eVals".

Compute the eigenvectors and eigenvalues, both returned as matrices: eigenvectors are the columns, and eigenvalues.

Note:: Warning: Only the real part of complex eigenvectors and eigenvalues are returned.

See also:: eigenVectorsSymmetric, eigenVectorsVec

EIGEN_STRONG_INLINE bool Eigen::MatrixBase::empty ( ) const [inline, inherited]

Definition at line 504 of file Core.

EIGEN_STRONG_INLINE iterator Eigen::MatrixBase::end ( ) [inline, inherited]

Definition at line 48 of file Core.

EIGEN_STRONG_INLINE const_iterator Eigen::MatrixBase::end ( ) const [inline, inherited]

Definition at line 50 of file Core.

Matrix<Scalar,3,1> Eigen::MatrixBase::eulerAngles	(	Index	a0,
		Index	a1,
		Index	a2
	)		const `[inherited]`

Returns:: the Euler-angles of the rotation matrix *this using the convention defined by the triplet (a0,a1,a2)

Each of the three parameters a0,a1,a2 represents the respective rotation axis as an integer in {0,1,2}. For instance, in:

 Vector3f ea = mat.eulerAngles(2, 0, 2);

"2" represents the z axis and "0" the x axis, etc. The returned angles are such that we have the following equality:

 mat == AngleAxisf(ea[0], Vector3f::UnitZ())
      * AngleAxisf(ea[1], Vector3f::UnitX())
      * AngleAxisf(ea[2], Vector3f::UnitZ());

This corresponds to the right-multiply conventions (with right hand side frames).

const MatrixExponentialReturnValue<Derived> Eigen::MatrixBase::exp ( ) const [inherited]

EIGEN_STRONG_INLINE MatrixBase<Derived>& Eigen::MatrixBase::Exp ( ) [inline, inherited]

Definition at line 746 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::Exp ( ) const [inline, inherited]

Definition at line 747 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractCol	(	size_t	nCol,
		VECTOR &	v,
		size_t	startingRow = `0`
	)		const `[inline, inherited]`

Extract one column from the matrix into a column vector.

Definition at line 787 of file Core.

void Eigen::MatrixBase::extractCol	(	size_t	nCol,
		std::vector< T > &	v,
		size_t	startingRow = `0`
	)		const `[inline, inherited]`

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Definition at line 791 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractMatrix	(	const size_t	firstRow,
		const size_t	firstCol,
		MATRIX &	m
	)		const `[inline, inherited]`

Definition at line 797 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractMatrix	(	const size_t	firstRow,
		const size_t	firstCol,
		const size_t	nRows,
		const size_t	nCols,
		MATRIX &	m
	)		const `[inline, inherited]`

Definition at line 801 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractRow	(	size_t	nRow,
		Eigen::EigenBase< OtherDerived > &	v,
		size_t	startingCol = `0`
	)		const `[inline, inherited]`

Extract one row from the matrix into a row vector.

Definition at line 770 of file Core.

void Eigen::MatrixBase::extractRow	(	size_t	nRow,
		std::vector< T > &	v,
		size_t	startingCol = `0`
	)		const `[inline, inherited]`

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Definition at line 774 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractRowAsCol	(	size_t	nRow,
		VECTOR &	v,
		size_t	startingCol = `0`
	)		const `[inline, inherited]`

Extract one row from the matrix into a column vector.

Definition at line 780 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::extractSubmatrix	(	const size_t	row_first,
		const size_t	row_last,
		const size_t	col_first,
		const size_t	col_last,
		MATRIX &	out
	)		const `[inline, inherited]`

Get a submatrix, given its bounds: first & last column and row (inclusive).

Definition at line 809 of file Core.

void Eigen::MatrixBase::extractSubmatrixSymmetrical	(	const std::vector< size_t > &	indices,
		MATRIX &	out
	)		const `[inline, inherited]`

Get a submatrix from a square matrix, by collecting the elements M(idxs,idxs), where idxs is the sequence of indices passed as argument.

A perfect application of this method is in extracting covariance matrices of a subset of variables from the full covariance matrix.

See also:: extractSubmatrix, extractSubmatrixSymmetricalBlocks

Definition at line 852 of file Core.

void Eigen::MatrixBase::extractSubmatrixSymmetricalBlocks	(	const size_t	block_size,
		const std::vector< size_t > &	block_indices,
		MATRIX &	out
	)		const `[inline, inherited]`

Get a submatrix from a square matrix, by collecting the elements M(idxs,idxs), where idxs is a sequence {block_indices(i):block_indices(i)+block_size-1} for all "i" up to the size of block_indices.

A perfect application of this method is in extracting covariance matrices of a subset of variables from the full covariance matrix.

See also:: extractSubmatrix, extractSubmatrixSymmetrical

Definition at line 820 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::eye ( ) [inline, inherited]

Make the matrix an identity matrix.

Definition at line 84 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::fill ( const Scalar v ) [inline, inherited]

Fill all the elements with a given value

Definition at line 59 of file Core.

void Eigen::MatrixBase::find_index_max_value	(	size_t &	u,
		size_t &	v,
		Scalar &	valMax
	)		const `[inline, inherited]`

[VECTORS OR MATRICES] Finds the maximum value (and the corresponding zero-based index) from a given container.

Exceptions:

std::exception On an empty input vector

Definition at line 237 of file Core.

const ForceAlignedAccess<Derived> Eigen::MatrixBase::forceAlignedAccess ( ) const [inline, inherited]

Returns:: an expression of *this with forced aligned access

See also:: forceAlignedAccessIf(),class ForceAlignedAccess

ForceAlignedAccess<Derived> Eigen::MatrixBase::forceAlignedAccess ( ) [inline, inherited]

Returns:: an expression of *this with forced aligned access

See also:: forceAlignedAccessIf(), class ForceAlignedAccess

internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type Eigen::MatrixBase::forceAlignedAccessIf ( ) const [inline, inherited]

Returns:: an expression of *this with forced aligned access if Enable is true.

See also:: forceAlignedAccess(), class ForceAlignedAccess

internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type Eigen::MatrixBase::forceAlignedAccessIf ( ) [inline, inherited]

Returns:: an expression of *this with forced aligned access if Enable is true.

See also:: forceAlignedAccess(), class ForceAlignedAccess

bool Eigen::MatrixBase::fromMatlabStringFormat	(	const std::string &	s,
		bool	dumpErrorMsgToStdErr = `true`
	)		`[inherited]`

Read a matrix from a string in Matlab-like format, for example "[1 0 2; 0 4 -1]" The string must start with '[' and end with ']'.

Rows are separated by semicolons ';' and columns in each row by one or more whitespaces ' ', commas ',' or tabs ''.

This format is also used for CConfigFile::read_matrix.

This template method can be instantiated for matrices of the types: int, long, unsinged int, unsigned long, float, double, long double

Returns:: true on success. false if the string is malformed, and then the matrix will be resized to 0x0.

See also:: inMatlabFormat, CConfigFile::read_matrix

const FullPivHouseholderQR<PlainObject> Eigen::MatrixBase::fullPivHouseholderQr ( ) const [inherited]

Returns:: the full-pivoting Householder QR decomposition of *this.

See also:: class FullPivHouseholderQR

const FullPivLU<PlainObject> Eigen::MatrixBase::fullPivLu ( ) const [inherited]

Returns:: the full-pivoting LU decomposition of *this.

See also:: class FullPivLU

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::get_unsafe	(	const size_t	row,
		const size_t	col
	)		const `[inline, inherited]`

Read-only access to one element (Use with caution, bounds are not checked!)

Definition at line 103 of file Core.

EIGEN_STRONG_INLINE Scalar& Eigen::MatrixBase::get_unsafe	(	const size_t	row,
		const size_t	col
	)		`[inline, inherited]`

Reference access to one element (Use with caution, bounds are not checked!)

Definition at line 111 of file Core.

EIGEN_STRONG_INLINE Scalar* Eigen::MatrixBase::get_unsafe_row ( size_t row ) [inline, inherited]

Fast but unsafe method to obtain a pointer to a given row of the matrix (Use only in time critical applications) VERY IMPORTANT WARNING: You must be aware of the memory layout, either Column or Row-major ordering.

Definition at line 99 of file Core.

EIGEN_STRONG_INLINE const Scalar* Eigen::MatrixBase::get_unsafe_row ( size_t row ) const [inline, inherited]

Definition at line 100 of file Core.

EIGEN_STRONG_INLINE size_t Eigen::MatrixBase::getColCount ( ) const [inline, inherited]

Get number of columns.

Definition at line 69 of file Core.

EIGEN_STRONG_INLINE size_t Eigen::MatrixBase::getRowCount ( ) const [inline, inherited]

Get number of rows.

Definition at line 67 of file Core.

const HNormalizedReturnType Eigen::MatrixBase::hnormalized ( ) const [inherited]

Returns:: an expression of the homogeneous normalized vector of *this

Example:

Output:

See also:: VectorwiseOp::hnormalized()

HomogeneousReturnType Eigen::MatrixBase::homogeneous ( ) const [inherited]

Returns:: an expression of the equivalent homogeneous vector

Example:

Output:

See also:: class Homogeneous

const HouseholderQR<PlainObject> Eigen::MatrixBase::householderQr ( ) const [inherited]

Returns:: the Householder QR decomposition of *this.

See also:: class HouseholderQR

RealScalar Eigen::MatrixBase::hypotNorm ( ) const [inherited]

Returns:: the l2 norm of *this avoiding undeflow and overflow. This version use a concatenation of hypot() calls, and it is very slow.

See also:: norm(), stableNorm()

static const IdentityReturnType Eigen::MatrixBase::Identity ( ) [static, inherited]

Returns:: an expression of the identity matrix (not necessarily square).

This variant is only for fixed-size MatrixBase types. For dynamic-size types, you need to use the variant taking size arguments.

Example:

Output:

See also:: Identity(Index,Index), setIdentity(), isIdentity()

static const IdentityReturnType Eigen::MatrixBase::Identity	(	Index	rows,
		Index	cols
	)		`[static, inherited]`

Returns:: an expression of the identity matrix (not necessarily square).

The parameters rows and cols are the number of rows and of columns of the returned matrix. Must be compatible with this MatrixBase type.

This variant is meant to be used for dynamic-size matrix types. For fixed-size types, it is redundant to pass rows and cols as arguments, so Identity() should be used instead.

Example:

Output:

See also:: Identity(), setIdentity(), isIdentity()

const ImagReturnType Eigen::MatrixBase::imag ( ) const [inline, inherited]

Returns:: an read-only expression of the imaginary part of *this.

See also:: real()

Definition at line 132 of file Core.

NonConstImagReturnType Eigen::MatrixBase::imag ( ) [inline, inherited]

Returns:: a non const expression of the imaginary part of *this.

See also:: real()

Definition at line 188 of file Core.

std::string Eigen::MatrixBase::inMatlabFormat ( const size_t decimal_digits = 6 ) const [inherited]

Dump matrix in matlab format.

This template method can be instantiated for matrices of the types: int, long, unsinged int, unsigned long, float, double, long double

See also:: fromMatlabStringFormat

EIGEN_STRONG_INLINE void Eigen::MatrixBase::insertCol	(	size_t	nCol,
		const MAT &	aCol
	)		`[inline, inherited]`

Definition at line 427 of file Core.

void Eigen::MatrixBase::insertCol	(	size_t	nCol,
		const std::vector< R > &	aCol
	)		`[inline, inherited]`

Definition at line 435 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::insertMatrix	(	size_t	r,
		size_t	c,
		const MAT &	m
	)		`[inline, inherited]`

Insert matrix "m" into this matrix at indices (r,c), that is, (*this)(r,c)=m(0,0) and so on.

Definition at line 421 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::insertMatrixTranspose	(	size_t	r,
		size_t	c,
		const MAT &	m
	)		`[inline, inherited]`

Definition at line 424 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::insertRow	(	size_t	nRow,
		const MAT &	aRow
	)		`[inline, inherited]`

Definition at line 426 of file Core.

void Eigen::MatrixBase::insertRow	(	size_t	nRow,
		const std::vector< R > &	aRow
	)		`[inline, inherited]`

Definition at line 429 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::inv ( ) const [inline, inherited]

Definition at line 493 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::inv ( MATRIX & outMat ) const [inline, inherited]

Definition at line 494 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::inv_fast ( MATRIX & outMat ) const [inline, inherited]

Definition at line 495 of file Core.

const internal::inverse_impl<Derived> Eigen::MatrixBase::inverse ( ) const [inherited]

Returns:: the matrix inverse of this matrix.

For small fixed sizes up to 4x4, this method uses cofactors. In the general case, this method uses class PartialPivLU.

Note:

This matrix must be invertible, otherwise the result is undefined. If you need an invertibility check, do the following:

for fixed sizes up to 4x4, use computeInverseAndDetWithCheck().
for the general case, use class FullPivLU.

Example:

Output:

See also:: computeInverseAndDetWithCheck()

bool Eigen::MatrixBase::isDiagonal ( RealScalar prec = NumTraits<Scalar>::dummy_precision() ) const [inherited]

Returns:: true if *this is approximately equal to a diagonal matrix, within the precision given by prec.

Example:

Output:

See also:: asDiagonal()

EIGEN_STRONG_INLINE bool Eigen::MatrixBase::isDiagonal ( ) const [inline, inherited]

Checks for matrix type.

Definition at line 360 of file Core.

bool Eigen::MatrixBase::isIdentity ( RealScalar prec = NumTraits<Scalar>::dummy_precision() ) const [inherited]

Returns:: true if *this is approximately equal to the identity matrix (not necessarily square), within the precision given by prec.

Example:

Output:

See also:: class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity()

bool Eigen::MatrixBase::isLowerTriangular ( RealScalar prec = NumTraits<Scalar>::dummy_precision() ) const [inherited]

Returns:: true if *this is approximately equal to a lower triangular matrix, within the precision given by prec.

See also:: isUpperTriangular()

bool Eigen::MatrixBase::isOrthogonal	(	const MatrixBase< OtherDerived > &	other,
		RealScalar	prec = `NumTraits<Scalar>::dummy_precision()`
	)		const `[inherited]`

Returns:: true if *this is approximately orthogonal to other, within the precision given by prec.

Example:

Output:

EIGEN_STRONG_INLINE bool Eigen::MatrixBase::isSingular ( const Scalar absThreshold = 0 ) const [inline, inherited]

Definition at line 134 of file Core.

EIGEN_STRONG_INLINE bool Eigen::MatrixBase::isSquare ( ) const [inline, inherited]

Definition at line 133 of file Core.

bool Eigen::MatrixBase::isUnitary ( RealScalar prec = NumTraits<Scalar>::dummy_precision() ) const [inherited]

Returns:: true if *this is approximately an unitary matrix, within the precision given by prec. In the case where the Scalar type is real numbers, a unitary matrix is an orthogonal matrix, whence the name.

Note:: This can be used to check whether a family of vectors forms an orthonormal basis. Indeed, m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an orthonormal basis.

Example:

Output:

bool Eigen::MatrixBase::isUpperTriangular ( RealScalar prec = NumTraits<Scalar>::dummy_precision() ) const [inherited]

Returns:: true if *this is approximately equal to an upper triangular matrix, within the precision given by prec.

See also:: isLowerTriangular()

JacobiSVD<PlainObject> Eigen::MatrixBase::jacobiSvd ( unsigned int computationOptions = 0 ) const [inherited]

EIGEN_STRONG_INLINE void Eigen::MatrixBase::laplacian ( Eigen::MatrixBase< OtherDerived > & ret ) const [inline, inherited]

Computes the laplacian of this square graph weight matrix.

The laplacian matrix is L = D - W, with D a diagonal matrix with the degree of each node, W the

Definition at line 284 of file Core.

void Eigen::MatrixBase::largestEigenvector	(	OUTVECT &	x,
		Scalar	resolution = `Scalar(0.01)`,
		size_t	maxIterations = `6`,
		int *	out_Iterations = `NULL`,
		float *	out_estimatedResolution = `NULL`
	)		const `[inline, inherited]`

Efficiently computes only the biggest eigenvector of the matrix using the Power Method, and returns it in the passed vector "x".

Definition at line 320 of file Core.

const LazyProductReturnType<Derived,OtherDerived>::Type Eigen::MatrixBase::lazyProduct ( const MatrixBase< OtherDerived > & other ) const [inherited]

Returns:: an expression of the matrix product of *this and other without implicit evaluation.

The returned product will behave like any other expressions: the coefficients of the product will be computed once at a time as requested. This might be useful in some extremely rare cases when only a small and no coherent fraction of the result's coefficients have to be computed.

Warning:: This version of the matrix product can be much much slower. So use it only if you know what you are doing and that you measured a true speed improvement.

See also:: operator*(const MatrixBase&)

const LDLT<PlainObject> Eigen::MatrixBase::ldlt ( ) const [inherited]

Returns:: the Cholesky decomposition with full pivoting without square root of *this

EIGEN_STRONG_INLINE void Eigen::MatrixBase::leftDivideSquare	(	const MAT2 &	A,
		MAT3 &	RES
	)		const `[inline, inherited]`

Matrix left divide: RES = A^-1 * this , with A being squared (using the Eigen::ColPivHouseholderQR method)

Definition at line 640 of file Core.

const _LhsNested& Eigen::CoeffBasedProduct::lhs ( ) const [inline]

Definition at line 214 of file Core.

const LLT<PlainObject> Eigen::MatrixBase::llt ( ) const [inherited]

Returns:: the LLT decomposition of *this

void Eigen::MatrixBase::loadFromTextFile ( const std::string & file ) [inherited]

Load matrix from a text file, compatible with MATLAB text format.

Lines starting with '%' or '#' are interpreted as comments and ignored.

See also:: saveToTextFile, fromMatlabStringFormat

void Eigen::MatrixBase::loadFromTextFile ( std::istream & _input_text_stream ) [inherited]

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

const MatrixLogarithmReturnValue<Derived> Eigen::MatrixBase::log ( ) const [inherited]

EIGEN_STRONG_INLINE MatrixBase<Derived>& Eigen::MatrixBase::Log ( ) [inline, inherited]

Definition at line 743 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::Log ( ) const [inline, inherited]

Definition at line 744 of file Core.

RealScalar Eigen::MatrixBase::lpNorm ( ) const [inherited]

Returns:: the $\ell^p$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values of the coefficients of *this. If p is the special value Eigen::Infinity, this function returns the $\ell^\infty$ norm, that is the maximum of the absolute values of the coefficients of *this.

See also:: norm()

const PartialPivLU<PlainObject> Eigen::MatrixBase::lu ( ) const [inherited]

Synonym of partialPivLu().

Returns:: the partial-pivoting LU decomposition of *this.

See also:: class PartialPivLU

void Eigen::MatrixBase::makeHouseholder	(	EssentialPart &	essential,
		Scalar &	tau,
		RealScalar &	beta
	)		const `[inherited]`

Computes the elementary reflector H such that: $ H *this = [ beta 0 ... 0]^T $ where the transformation H is: $ H = I - tau v v^*$ and the vector v is: $ v^T = [1 essential^T] $ .

On output:

Parameters:

essential	the essential part of the vector `v`
tau	the scaling factor of the householder transformation
beta	the result of H * `*this`

See also:: MatrixBase::makeHouseholderInPlace(), MatrixBase::applyHouseholderOnTheLeft(), MatrixBase::applyHouseholderOnTheRight()

void Eigen::MatrixBase::makeHouseholderInPlace	(	Scalar &	tau,
		RealScalar &	beta
	)		`[inherited]`

MatrixBase<Derived>& Eigen::MatrixBase::matrix ( ) [inline, inherited]

Definition at line 327 of file Core.

const MatrixBase<Derived>& Eigen::MatrixBase::matrix ( ) const [inline, inherited]

Definition at line 328 of file Core.

const MatrixFunctionReturnValue<Derived> Eigen::MatrixBase::matrixFunction ( StemFunction f ) const [inherited]

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::maximum ( ) const [inline, inherited]

[VECTORS OR MATRICES] Finds the maximum value

Exceptions:

std::exception On an empty input container

Definition at line 195 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::maximum ( size_t * maxIndex ) const [inline, inherited]

[VECTORS ONLY] Finds the maximum value (and the corresponding zero-based index) from a given container.

Exceptions:

std::exception On an empty input vector

Definition at line 225 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::maximumDiagonal ( ) const [inline, inherited]

Finds the maximum value in the diagonal of the matrix.

Definition at line 370 of file Core.

EIGEN_STRONG_INLINE double Eigen::MatrixBase::mean ( ) const [inline, inherited]

Computes the mean of the entire matrix.

See also:: meanAndStdAll

Definition at line 374 of file Core.

void Eigen::MatrixBase::meanAndStd	(	VEC &	outMeanVector,
		VEC &	outStdVector,
		const bool	unbiased_variance = `true`
	)		const `[inline, inherited]`

Computes a row with the mean values of each column in the matrix and the associated vector with the standard deviation of each column.

See also:: mean,meanAndStdAll

Exceptions:

std::exception If the matrix/vector is empty.

Parameters:

unbiased_variance Standard deviation is sum(vals-mean)/K, with K=N-1 or N for unbiased_variance=true or false, respectively.

Definition at line 385 of file Core.

void Eigen::MatrixBase::meanAndStdAll	(	double &	outMean,
		double &	outStd,
		const bool	unbiased_variance = `true`
	)		const `[inline, inherited]`

Computes the mean and standard deviation of all the elements in the matrix as a whole.

See also:: mean,meanAndStd

Exceptions:

std::exception If the matrix/vector is empty.

Parameters:

unbiased_variance Standard deviation is sum(vals-mean)/K, with K=N-1 or N for unbiased_variance=true or false, respectively.

Definition at line 407 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::minimum ( ) const [inline, inherited]

[VECTORS OR MATRICES] Finds the minimum value

See also:: maximum, minimum_maximum

Exceptions:

std::exception On an empty input container

Definition at line 204 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::minimum ( size_t * minIndex ) const [inline, inherited]

[VECTORS ONLY] Finds the minimum value (and the corresponding zero-based index) from a given container.

See also:: maximum, minimum_maximum

Exceptions:

std::exception On an empty input vector

Definition at line 249 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::minimum_maximum	(	Scalar &	out_min,
		Scalar &	out_max
	)		const `[inline, inherited]`

[VECTORS OR MATRICES] Compute the minimum and maximum of a container at once

See also:: maximum, minimum

Exceptions:

std::exception On an empty input container

Definition at line 213 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::minimum_maximum	(	Scalar &	out_min,
		Scalar &	out_max,
		size_t *	minIndex,
		size_t *	maxIndex
	)		const `[inline, inherited]`

[VECTORS ONLY] Compute the minimum and maximum of a container at once

See also:: maximum, minimum

Exceptions:

std::exception On an empty input vector

Definition at line 261 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply	(	const MATRIX1 &	A,
		const MATRIX2 &	B
	)		`[inline, inherited]`

Parameters:

B	this = A * B

Definition at line 524 of file Core.

void Eigen::MatrixBase::multiply_A_skew3	(	const MAT_A &	A,
		const SKEW_3VECTOR &	v
	)		`[inline, inherited]`

this = A * skew(v), with v being a 3-vector (or 3-array) and skew(v) the skew symmetric matrix of v (see mrpt::math::skew_symmetric3)

Definition at line 588 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AAt ( const MAT_A & A ) [inline, inherited]

Parameters:

A	this = A * A^T

Definition at line 623 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AAt_scalar	(	const MAT_A &	A,
		typename MAT_A::value_type	f
	)		`[inline, inherited]`

this = C * C^T * f (with a matrix C and a scalar f).

Definition at line 578 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AB	(	const MATRIX1 &	A,
		const MATRIX2 &	B
	)		`[inline, inherited]`

Parameters:

B	this = A * B

Definition at line 527 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_Ab	(	const OTHERVECTOR1 &	vIn,
		OTHERVECTOR2 &	vOut,
		bool	accumToOutput = `false`
	)		const `[inline, inherited]`

Computes the vector vOut = this * vIn, where "vIn" is a column vector of the appropriate length.

Definition at line 538 of file Core.

void Eigen::MatrixBase::multiply_ABC	(	const MAT_A &	A,
		const MAT_B &	B,
		const MAT_C &	C
	)		`[inline, inherited]`

Parameters:

C	this = ABC

Definition at line 603 of file Core.

void Eigen::MatrixBase::multiply_ABCt	(	const MAT_A &	A,
		const MAT_B &	B,
		const MAT_C &	C
	)		`[inline, inherited]`

Parameters:

C	this = AB(C^T)

Definition at line 608 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_ABt	(	const MAT_A &	A,
		const MAT_B &	B
	)		`[inline, inherited]`

Parameters:

B	this = A * B^T

Definition at line 618 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AtA ( const MAT_A & A ) [inline, inherited]

Parameters:

A	this = A^T * A

Definition at line 628 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AtA_scalar	(	const MAT_A &	A,
		typename MAT_A::value_type	f
	)		`[inline, inherited]`

this = C^T * C * f (with a matrix C and a scalar f).

Definition at line 583 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_AtB	(	const MATRIX1 &	A,
		const MATRIX2 &	B
	)		`[inline, inherited]`

Parameters:

B	this=A^t * B

Definition at line 532 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_Atb	(	const OTHERVECTOR1 &	vIn,
		OTHERVECTOR2 &	vOut,
		bool	accumToOutput = `false`
	)		const `[inline, inherited]`

Computes the vector vOut = this^T * vIn, where "vIn" is a column vector of the appropriate length.

Definition at line 545 of file Core.

void Eigen::MatrixBase::multiply_AtBC	(	const MAT_A &	A,
		const MAT_B &	B,
		const MAT_C &	C
	)		`[inline, inherited]`

Parameters:

C	this = A(^T)BC

Definition at line 613 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_HCHt	(	const MAT_C &	C,
		MAT_R &	R,
		bool	accumResultInOutput = `false`
	)		const `[inline, inherited]`

< R = this * C * this^T

Definition at line 551 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::multiply_HCHt_scalar ( const MAT_C & C ) const [inline, inherited]

R = H * C * H^T (with a vector H and a symmetric matrix C) In fact when H is a vector, multiply_HCHt_scalar and multiply_HtCH_scalar are exactly equivalent

Definition at line 566 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_HtCH	(	const MAT_C &	C,
		MAT_R &	R,
		bool	accumResultInOutput = `false`
	)		const `[inline, inherited]`

< R = this^T * C * this

Definition at line 558 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::multiply_HtCH_scalar ( const MAT_C & C ) const [inline, inherited]

R = H^T * C * H (with a vector H and a symmetric matrix C) In fact when H is a vector, multiply_HCHt_scalar and multiply_HtCH_scalar are exactly equivalent

Definition at line 572 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_result_is_symmetric	(	const MAT_A &	A,
		const MAT_B &	B
	)		`[inline, inherited]`

Parameters:

B	this = A * B (result is symmetric)

Definition at line 633 of file Core.

void Eigen::MatrixBase::multiply_skew3_A	(	const SKEW_3VECTOR &	v,
		const MAT_A &	A
	)		`[inline, inherited]`

this = skew(v)*A, with v being a 3-vector (or 3-array) and skew(v) the skew symmetric matrix of v (see mrpt::math::skew_symmetric3)

Definition at line 592 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiply_subMatrix	(	const MAT_A &	A,
		MAT_OUT &	outResult,
		const size_t	A_cols_offset,
		const size_t	A_rows_offset,
		const size_t	A_col_count
	)		const `[inline, inherited]`

outResult = this * A

Definition at line 598 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiplyColumnByScalar	(	size_t	c,
		Scalar	s
	)		`[inline, inherited]`

Definition at line 184 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::multiplyRowByScalar	(	size_t	r,
		Scalar	s
	)		`[inline, inherited]`

Definition at line 185 of file Core.

NoAlias<Derived,Eigen::MatrixBase > Eigen::MatrixBase::noalias ( ) [inherited]

Returns:: a pseudo expression of *this with an operator= assuming no aliasing between *this and the source expression.

More precisely, noalias() allows to bypass the EvalBeforeAssignBit flag. Currently, even though several expressions may alias, only product expressions have this flag. Therefore, noalias() is only usefull when the source expression contains a matrix product.

Here are some examples where noalias is usefull:

 D.noalias()  = A * B;
 D.noalias() += A.transpose() * B;
 D.noalias() -= 2 * A * B.adjoint();

On the other hand the following example will lead to a wrong result:

 A.noalias() = A * B;

because the result matrix A is also an operand of the matrix product. Therefore, there is no alternative than evaluating A * B in a temporary, that is the default behavior when you write:

 A = A * B;

See also:: class NoAlias

RealScalar Eigen::MatrixBase::norm ( ) const [inherited]

Returns:: , for vectors, the l2 norm of *this, and for matrices the Frobenius norm. In both cases, it consists in the square root of the sum of the square of all the matrix entries. For vectors, this is also equals to the square root of the dot product of *this with itself.

See also:: dot(), squaredNorm()

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::norm_inf ( ) const [inline, inherited]

Compute the norm-infinite of a vector ($f[ ||{v}||_ $f]), ie the maximum absolute value of the elements.

Definition at line 272 of file Core.

void Eigen::MatrixBase::normalize ( void ) [inherited]

Normalizes the vector, i.e.

divides it by its own norm.

See also:: norm(), normalized()

void Eigen::MatrixBase::normalize	(	Scalar	valMin,
		Scalar	valMax
	)		`[inline, inherited]`

Scales all elements such as the minimum & maximum values are shifted to the given values.

Definition at line 753 of file Core.

const PlainObject Eigen::MatrixBase::normalized ( ) const [inherited]

Returns:: an expression of the quotient of *this by its own norm.

See also:: norm(), normalize()

EIGEN_STRONG_INLINE void Eigen::MatrixBase::ones	(	const size_t	row,
		const size_t	col
	)		`[inline, inherited]`

Resize matrix and set all elements to one.

Definition at line 92 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::ones ( ) [inline, inherited]

Set all elements to one.

Definition at line 94 of file Core.

EIGEN_STRONG_INLINE Eigen::CoeffBasedProduct::operator const PlainObject & ( ) const [inline]

Definition at line 208 of file Core.

bool Eigen::MatrixBase::operator!= ( const MatrixBase< OtherDerived > & other ) const [inline, inherited]

Returns:: true if at least one pair of coefficients of *this and other are not exactly equal to each other.

Warning:: When using floating point scalar values you probably should rather use a fuzzy comparison such as isApprox()

See also:: isApprox(), operator==

Definition at line 311 of file Core.

const ScalarMultipleReturnType Eigen::MatrixBase::operator* ( const Scalar & scalar ) const [inline, inherited]

Returns:: an expression of *this scaled by the scalar factor scalar

Definition at line 65 of file Core.

const ScalarMultipleReturnType Eigen::MatrixBase::operator* ( const RealScalar & scalar ) const [inherited]

const CwiseUnaryOp<internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >, const Derived> Eigen::MatrixBase::operator* ( const std::complex< Scalar > & scalar ) const [inline, inherited]

Overloaded for efficient real matrix times complex scalar value.

Definition at line 85 of file Core.

const ProductReturnType<Derived,OtherDerived>::Type Eigen::MatrixBase::operator* ( const MatrixBase< OtherDerived > & other ) const [inherited]

Returns:: the matrix product of *this and other.

Note:: If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().

See also:: lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()

const DiagonalProduct<Derived, DiagonalDerived, OnTheRight> Eigen::MatrixBase::operator* ( const DiagonalBase< DiagonalDerived > & diagonal ) const [inherited]

Returns:: the diagonal matrix product of *this by the diagonal matrix diagonal.

ScalarMultipleReturnType Eigen::MatrixBase::operator* ( const UniformScaling< Scalar > & s ) const [inherited]

Concatenates a linear transformation matrix and a uniform scaling.

Derived& Eigen::MatrixBase::operator*= ( const EigenBase< OtherDerived > & other ) [inherited]

replaces *this by *this * other.

Returns:: a reference to *this

Derived& Eigen::MatrixBase::operator+= ( const MatrixBase< OtherDerived > & other ) [inherited]

replaces *this by *this + other.

Returns:: a reference to *this

Derived& Eigen::MatrixBase::operator+= ( const ArrayBase< OtherDerived > & ) [inline, protected, inherited]

Definition at line 515 of file Core.

const CwiseUnaryOp<internal::scalar_opposite_op<typename internal::traits<Derived>::Scalar>, const Derived> Eigen::MatrixBase::operator- ( ) const [inline, inherited]

Returns:: an expression of the opposite of *this

Definition at line 60 of file Core.

Derived& Eigen::MatrixBase::operator-= ( const MatrixBase< OtherDerived > & other ) [inherited]

replaces *this by *this - other.

Returns:: a reference to *this

Derived& Eigen::MatrixBase::operator-= ( const ArrayBase< OtherDerived > & ) [inline, protected, inherited]

Definition at line 518 of file Core.

const CwiseUnaryOp<internal::scalar_quotient1_op<typename internal::traits<Derived>::Scalar>, const Derived> Eigen::MatrixBase::operator/ ( const Scalar & scalar ) const [inline, inherited]

Returns:: an expression of *this divided by the scalar value scalar

Definition at line 77 of file Core.

bool Eigen::MatrixBase::operator== ( const MatrixBase< OtherDerived > & other ) const [inline, inherited]

Returns:: true if each coefficients of *this and other are all exactly equal.

Warning:: When using floating point scalar values you probably should rather use a fuzzy comparison such as isApprox()

See also:: isApprox(), operator!=

Definition at line 303 of file Core.

MatrixBase<Derived>& Eigen::MatrixBase::operator^= ( const unsigned int pow ) [inline, inherited]

Combined matrix power and assignment operator.

Definition at line 346 of file Core.

RealScalar Eigen::MatrixBase::operatorNorm ( ) const [inherited]

Computes the L2 operator norm.

Returns:: Operator norm of the matrix.

This function computes the L2 operator norm of a matrix, which is also known as the spectral norm. The norm of a matrix $ A $ is defined to be

$\|A\|_2 = \max_x \frac{\|Ax\|_2}{\|x\|_2}$

where the maximum is over all vectors and the norm on the right is the Euclidean vector norm. The norm equals the largest singular value, which is the square root of the largest eigenvalue of the positive semi-definite matrix $ A^*A $ .

The current implementation uses the eigenvalues of $ A^*A $ , as computed by SelfAdjointView::eigenvalues(), to compute the operator norm of a matrix. The SelfAdjointView class provides a better algorithm for selfadjoint matrices.

Example:

Output:

See also:: SelfAdjointView::eigenvalues(), SelfAdjointView::operatorNorm()

template<int LoadMode>

EIGEN_STRONG_INLINE const PacketScalar Eigen::CoeffBasedProduct::packet	(	Index	row,
		Index	col
	)		const `[inline]`

Definition at line 197 of file Core.

const PartialPivLU<PlainObject> Eigen::MatrixBase::partialPivLu ( ) const [inherited]

Returns:: the partial-pivoting LU decomposition of *this.

See also:: class PartialPivLU

EIGEN_STRONG_INLINE void Eigen::MatrixBase::push_back ( Scalar val ) [inline, inherited]

Insert an element at the end of the container (for 1D vectors/arrays)

Definition at line 126 of file Core.

EIGEN_STRONG_INLINE size_t Eigen::MatrixBase::rank ( double threshold = 0 ) const [inline, inherited]

Gets the rank of the matrix via the Eigen::ColPivHouseholderQR method.

Parameters:

threshold If set to >0, it's used as threshold instead of Eigen's default one.

Definition at line 723 of file Core.

RealReturnType Eigen::MatrixBase::real ( ) const [inline, inherited]

Returns:: a read-only expression of the real part of *this.

See also:: imag()

Definition at line 126 of file Core.

NonConstRealReturnType Eigen::MatrixBase::real ( ) [inline, inherited]

Returns:: a non const expression of the real part of *this.

See also:: imag()

Definition at line 182 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::removeColumns ( const std::vector< size_t > & idxsToRemove ) [inline, inherited]

Remove columns of the matrix.

Definition at line 443 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::removeRows ( const std::vector< size_t > & idxsToRemove ) [inline, inherited]

Remove rows of the matrix.

Definition at line 467 of file Core.

const _RhsNested& Eigen::CoeffBasedProduct::rhs ( ) const [inline]

Definition at line 215 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::rightDivideSquare	(	const MAT2 &	B,
		MAT3 &	RES
	)		const `[inline, inherited]`

Matrix right divide: RES = this * B^-1, with B being squared (using the Eigen::ColPivHouseholderQR method)

Definition at line 649 of file Core.

EIGEN_STRONG_INLINE Index Eigen::CoeffBasedProduct::rows ( void ) const [inline]

Definition at line 174 of file Core.

void Eigen::MatrixBase::saveToTextFile	(	const std::string &	file,
		mrpt::math::TMatrixTextFileFormat	fileFormat = `mrpt::math::MATRIX_FORMAT_ENG`,
		bool	appendMRPTHeader = `false`,
		const std::string &	userHeader = `std::string()`
	)		const `[inherited]`

Save matrix to a text file, compatible with MATLAB text format (see also the methods of matrix classes themselves).

Parameters:

theMatrix	It can be a CMatrixTemplate or a CMatrixFixedNumeric.
file	The target filename.
fileFormat	See TMatrixTextFileFormat. The format of the numbers in the text file.
appendMRPTHeader	Insert this header to the file "% File generated by MRPT. Load with MATLAB with: VAR=load(FILENAME);"
userHeader	Additional text to be written at the head of the file. Typically MALAB comments "% This file blah blah". Final end-of-line is not needed.

See also:: loadFromTextFile, CMatrixTemplate::inMatlabFormat, SAVE_MATRIX

EIGEN_STRONG_INLINE void Eigen::MatrixBase::scalarPow ( const Scalar s ) [inline, inherited]

Scalar power of all elements to a given power, this is diferent of ^ operator.

Definition at line 357 of file Core.

SelfAdjointViewReturnType<UpLo>::Type Eigen::MatrixBase::selfadjointView ( ) [inherited]

ConstSelfAdjointViewReturnType<UpLo>::Type Eigen::MatrixBase::selfadjointView ( ) const [inherited]

EIGEN_STRONG_INLINE void Eigen::MatrixBase::set_unsafe	(	const size_t	row,
		const size_t	col,
		const Scalar	val
	)		`[inline, inherited]`

Sets an element (Use with caution, bounds are not checked!)

Definition at line 118 of file Core.

Derived& Eigen::MatrixBase::setIdentity ( ) [inherited]

Writes the identity expression (not necessarily square) into *this.

Example:

Output:

See also:: class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()

Derived& Eigen::MatrixBase::setIdentity	(	Index	rows,
		Index	cols
	)		`[inherited]`

Resizes to the given size, and writes the identity expression (not necessarily square) into *this.

Parameters:

rows	the new number of rows
cols	the new number of columns

Example:

Output:

See also:: MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()

EIGEN_STRONG_INLINE void Eigen::MatrixBase::setSize	(	size_t	row,
		size_t	col
	)		`[inline, inherited]`

Changes the size of matrix, maintaining its previous content as possible and padding with zeros where applicable.

**WARNING**: MRPT's add-on method setSize() pads with zeros, while Eigen's resize() does NOT (new elements are undefined).

Definition at line 301 of file Core.

const MatrixFunctionReturnValue<Derived> Eigen::MatrixBase::sin ( ) const [inherited]

const MatrixFunctionReturnValue<Derived> Eigen::MatrixBase::sinh ( ) const [inherited]

const SparseView<Derived> Eigen::MatrixBase::sparseView	(	const Scalar &	m_reference = `Scalar(0)`,
		typename NumTraits< Scalar >::Real	m_epsilon = `NumTraits<Scalar>::dummy_precision()`
	)		const `[inherited]`

const MatrixSquareRootReturnValue<Derived> Eigen::MatrixBase::sqrt ( ) const [inherited]

EIGEN_STRONG_INLINE MatrixBase<Derived>& Eigen::MatrixBase::Sqrt ( ) [inline, inherited]

Definition at line 737 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::Sqrt ( ) const [inline, inherited]

Definition at line 738 of file Core.

EIGEN_STRONG_INLINE MatrixBase<Derived>& Eigen::MatrixBase::Square ( ) [inline, inherited]

Definition at line 749 of file Core.

EIGEN_STRONG_INLINE PlainObject Eigen::MatrixBase::Square ( ) const [inline, inherited]

Definition at line 750 of file Core.

RealScalar Eigen::MatrixBase::squaredNorm ( ) const [inherited]

Returns:: , for vectors, the squared l2 norm of *this, and for matrices the Frobenius norm. In both cases, it consists in the sum of the square of all the matrix entries. For vectors, this is also equals to the dot product of *this with itself.

See also:: dot(), norm()

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::squareNorm ( ) const [inline, inherited]

Compute the square norm of a vector/array/matrix (the Euclidean distance to the origin, taking all the elements as a single vector).

See also:: norm

Definition at line 275 of file Core.

RealScalar Eigen::MatrixBase::stableNorm ( ) const [inherited]

Returns:: the l2 norm of *this avoiding underflow and overflow. This version use a blockwise two passes algorithm: 1 - find the absolute largest coefficient s 2 - compute $s \Vert \frac{*this}{s} \Vert$ in a standard way

For architecture/scalar types supporting vectorization, this version is faster than blueNorm(). Otherwise the blueNorm() is much faster.

See also:: norm(), blueNorm(), hypotNorm()

EIGEN_STRONG_INLINE void Eigen::MatrixBase::substract_AAt ( const OTHERMATRIX & A ) [inline, inherited]

this -= A + A^T

Definition at line 521 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::substract_Ac	(	const OTHERMATRIX &	m,
		const Scalar	c
	)		`[inline, inherited]`

Substract c (scalar) times A to this matrix: this -= A * c

Definition at line 509 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::substract_An	(	const OTHERMATRIX &	m,
		const size_t	n
	)		`[inline, inherited]`

Substract n (integer) times A to this matrix: this -= A * n

Definition at line 515 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::substract_At ( const OTHERMATRIX & m ) [inline, inherited]

Substract A transposed to this matrix: this -= A.adjoint()

Definition at line 512 of file Core.

EIGEN_STRONG_INLINE Scalar Eigen::MatrixBase::sumAll ( ) const [inline, inherited]

Sum all the elements, returning a value of the same type than the container

Definition at line 278 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::swapCols	(	size_t	i1,
		size_t	i2
	)		`[inline, inherited]`

Definition at line 187 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::swapRows	(	size_t	i1,
		size_t	i2
	)		`[inline, inherited]`

Definition at line 188 of file Core.

EIGEN_STRONG_INLINE const AdjointReturnType Eigen::MatrixBase::t ( ) const [inline, inherited]

Transpose.

Definition at line 491 of file Core.

Scalar Eigen::MatrixBase::trace ( ) const [inherited]

Returns:: the trace of *this, i.e. the sum of the coefficients on the main diagonal.

*this can be any matrix, not necessarily square.

See also:: diagonal(), sum()

TriangularViewReturnType<Mode>::Type Eigen::MatrixBase::triangularView ( ) [inherited]

Returns:: an expression of a triangular view extracted from the current matrix

The parameter Mode can have the following values: #Upper, #StrictlyUpper, #UnitUpper, #Lower, #StrictlyLower, #UnitLower.

Example:

Output:

See also:: class TriangularView

ConstTriangularViewReturnType<Mode>::Type Eigen::MatrixBase::triangularView ( ) const [inherited]

This is the const version of MatrixBase::triangularView()

const CwiseUnaryOp<CustomUnaryOp, const Derived> Eigen::MatrixBase::unaryExpr ( const CustomUnaryOp & func = CustomUnaryOp() ) const [inline, inherited]

Apply a unary operator coefficient-wise.

Parameters:

[in] func Functor implementing the unary operator

Template Parameters:

CustomUnaryOp Type of func

Returns:: An expression of a custom coefficient-wise unary operator func of *this

The function ptr_fun() from the C++ standard library can be used to make functors out of normal functions.

Example:

Output:

Genuine functors allow for more possibilities, for instance it may contain a state.

Example:

Output:

See also:: class CwiseUnaryOp, class CwiseBinaryOp

Definition at line 155 of file Core.

const CwiseUnaryView<CustomViewOp, const Derived> Eigen::MatrixBase::unaryViewExpr ( const CustomViewOp & func = CustomViewOp() ) const [inline, inherited]

Returns:: an expression of a custom coefficient-wise unary operator func of *this

The template parameter CustomUnaryOp is the type of the functor of the custom unary operator.

Example:

Output:

See also:: class CwiseUnaryOp, class CwiseBinaryOp

Definition at line 173 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::unit	(	const size_t	nRows,
		const Scalar	diag_vals
	)		`[inline, inherited]`

Make the matrix an identity matrix (the diagonal values can be 1.0 or any other value)

Definition at line 72 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::unit ( ) [inline, inherited]

Make the matrix an identity matrix.

Definition at line 82 of file Core.

static const BasisReturnType Eigen::MatrixBase::Unit	(	Index	size,
		Index	i
	)		`[static, inherited]`

Returns:: an expression of the i-th unit (basis) vector.

See also:: MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

static const BasisReturnType Eigen::MatrixBase::Unit ( Index i ) [static, inherited]

Returns:: an expression of the i-th unit (basis) vector.

This variant is for fixed-size vector only.

See also:: MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

PlainObject Eigen::MatrixBase::unitOrthogonal ( void ) const [inherited]

Returns:: a unit vector which is orthogonal to *this

The size of *this must be at least 2. If the size is exactly 2, then the returned vector is a counter clock wise rotation of *this, i.e., (-y,x).normalized().

See also:: cross()

static const BasisReturnType Eigen::MatrixBase::UnitW ( ) [static, inherited]

Returns:: an expression of the W axis unit vector (0,0,0,1)

See also:: MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

static const BasisReturnType Eigen::MatrixBase::UnitX ( ) [static, inherited]

Returns:: an expression of the X axis unit vector (1{,0}^*)

See also:: MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

static const BasisReturnType Eigen::MatrixBase::UnitY ( ) [static, inherited]

Returns:: an expression of the Y axis unit vector (0,1{,0}^*)

See also:: MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

static const BasisReturnType Eigen::MatrixBase::UnitZ ( ) [static, inherited]

Returns:: an expression of the Z axis unit vector (0,0,1{,0}^*)

See also:: MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()

EIGEN_STRONG_INLINE void Eigen::MatrixBase::unsafeRemoveColumns ( const std::vector< size_t > & idxs ) [inline, inherited]

Remove columns of the matrix.

The unsafe version assumes that, the indices are sorted in ascending order.

Definition at line 454 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::unsafeRemoveRows ( const std::vector< size_t > & idxs ) [inline, inherited]

Remove rows of the matrix.

The unsafe version assumes that, the indices are sorted in ascending order.

Definition at line 478 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::zeros ( ) [inline, inherited]

Set all elements to zero.

Definition at line 87 of file Core.

EIGEN_STRONG_INLINE void Eigen::MatrixBase::zeros	(	const size_t	row,
		const size_t	col
	)		`[inline, inherited]`

Resize and set all elements to zero.

Definition at line 89 of file Core.

Friends And Related Function Documentation

const ScalarMultipleReturnType operator*	(	const Scalar &	scalar,
		const StorageBaseType &	matrix
	)		`[friend, inherited]`

Definition at line 92 of file Core.

const CwiseUnaryOp<internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >, const Derived> operator*	(	const std::complex< Scalar > &	scalar,
		const StorageBaseType &	matrix
	)		`[friend, inherited]`

Definition at line 96 of file Core.

Member Data Documentation

const LhsNested Eigen::CoeffBasedProduct::m_lhs [protected]

Definition at line 228 of file Core.

PlainObject Eigen::CoeffBasedProduct::m_result [mutable, protected]

Definition at line 231 of file Core.

const RhsNested Eigen::CoeffBasedProduct::m_rhs [protected]

Definition at line 229 of file Core.