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Eigen
3.3.3
|
Base class for all dense matrices, vectors, and arrays.
This class is the base that is inherited by all dense objects (matrix, vector, arrays, and related expression types). The common Eigen API for dense objects is contained in this class.
Derived | is the derived type, e.g., a matrix type or an expression. |
This class can be extended with the help of the plugin mechanism described on the page Extending MatrixBase (and other classes) by defining the preprocessor symbol EIGEN_DENSEBASE_PLUGIN
.
Public Types | |
enum | { RowsAtCompileTime, ColsAtCompileTime, SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime, IsVectorAtCompileTime, Flags, IsRowMajor } |
typedef Array< typename internal::traits< Derived > ::Scalar, internal::traits < Derived >::RowsAtCompileTime, internal::traits< Derived > ::ColsAtCompileTime, AutoAlign|(internal::traits < Derived >::Flags &RowMajorBit?RowMajor:ColMajor), internal::traits< Derived > ::MaxRowsAtCompileTime, internal::traits< Derived > ::MaxColsAtCompileTime > | PlainArray |
typedef Matrix< typename internal::traits< Derived > ::Scalar, internal::traits < Derived >::RowsAtCompileTime, internal::traits< Derived > ::ColsAtCompileTime, AutoAlign|(internal::traits < Derived >::Flags &RowMajorBit?RowMajor:ColMajor), internal::traits< Derived > ::MaxRowsAtCompileTime, internal::traits< Derived > ::MaxColsAtCompileTime > | PlainMatrix |
typedef internal::conditional < internal::is_same< typename internal::traits< Derived > ::XprKind, MatrixXpr >::value, PlainMatrix, PlainArray > ::type | PlainObject |
The plain matrix or array type corresponding to this expression. | |
typedef internal::traits < Derived >::Scalar | Scalar |
typedef internal::traits < Derived >::StorageIndex | StorageIndex |
The type used to store indices. | |
typedef Scalar | value_type |
Public Member Functions | |
bool | all () const |
bool | allFinite () const |
bool | any () const |
BlockXpr | block (Index startRow, Index startCol, Index blockRows, Index blockCols) |
const ConstBlockXpr | block (Index startRow, Index startCol, Index blockRows, Index blockCols) const |
This is the const version of block(Index,Index,Index,Index). */. | |
template<int NRows, int NCols> | |
FixedBlockXpr< NRows, NCols >::Type | block (Index startRow, Index startCol) |
template<int NRows, int NCols> | |
const ConstFixedBlockXpr < NRows, NCols >::Type | block (Index startRow, Index startCol) const |
This is the const version of block<>(Index, Index). */. | |
template<int NRows, int NCols> | |
FixedBlockXpr< NRows, NCols >::Type | block (Index startRow, Index startCol, Index blockRows, Index blockCols) |
template<int NRows, int NCols> | |
const ConstFixedBlockXpr < NRows, NCols >::Type | block (Index startRow, Index startCol, Index blockRows, Index blockCols) const |
This is the const version of block<>(Index, Index, Index, Index). | |
BlockXpr | bottomLeftCorner (Index cRows, Index cCols) |
const ConstBlockXpr | bottomLeftCorner (Index cRows, Index cCols) const |
This is the const version of bottomLeftCorner(Index, Index). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | bottomLeftCorner () |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | bottomLeftCorner () const |
This is the const version of bottomLeftCorner<int, int>(). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | bottomLeftCorner (Index cRows, Index cCols) |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | bottomLeftCorner (Index cRows, Index cCols) const |
This is the const version of bottomLeftCorner<int, int>(Index, Index). | |
BlockXpr | bottomRightCorner (Index cRows, Index cCols) |
const ConstBlockXpr | bottomRightCorner (Index cRows, Index cCols) const |
This is the const version of bottomRightCorner(Index, Index). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | bottomRightCorner () |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | bottomRightCorner () const |
This is the const version of bottomRightCorner<int, int>(). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | bottomRightCorner (Index cRows, Index cCols) |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | bottomRightCorner (Index cRows, Index cCols) const |
This is the const version of bottomRightCorner<int, int>(Index, Index). | |
RowsBlockXpr | bottomRows (Index n) |
ConstRowsBlockXpr | bottomRows (Index n) const |
This is the const version of bottomRows(Index). | |
template<int N> | |
NRowsBlockXpr< N >::Type | bottomRows (Index n=N) |
template<int N> | |
ConstNRowsBlockXpr< N >::Type | bottomRows (Index n=N) const |
This is the const version of bottomRows<int>(). | |
ColXpr | col (Index i) |
ConstColXpr | col (Index i) const |
This is the const version of col(). | |
ConstColwiseReturnType | colwise () const |
ColwiseReturnType | colwise () |
Index | count () const |
EvalReturnType | eval () const |
void | fill (const Scalar &value) |
template<unsigned int Added, unsigned int Removed> | |
EIGEN_DEPRECATED const Derived & | flagged () const |
const WithFormat< Derived > | format (const IOFormat &fmt) const |
bool | hasNaN () const |
SegmentReturnType | head (Index n) |
ConstSegmentReturnType | head (Index n) const |
This is the const version of head(Index). | |
template<int N> | |
FixedSegmentReturnType< N >::Type | head (Index n=N) |
template<int N> | |
ConstFixedSegmentReturnType< N > ::Type | head (Index n=N) const |
This is the const version of head<int>(). | |
Index | innerSize () const |
template<typename OtherDerived > | |
bool | isApprox (const DenseBase< OtherDerived > &other, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
bool | isApproxToConstant (const Scalar &value, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
bool | isConstant (const Scalar &value, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
template<typename Derived > | |
bool | isMuchSmallerThan (const typename NumTraits< Scalar >::Real &other, const RealScalar &prec) const |
template<typename OtherDerived > | |
bool | isMuchSmallerThan (const DenseBase< OtherDerived > &other, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
bool | isOnes (const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
bool | isZero (const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const |
template<typename OtherDerived > | |
Derived & | lazyAssign (const DenseBase< OtherDerived > &other) |
ColsBlockXpr | leftCols (Index n) |
ConstColsBlockXpr | leftCols (Index n) const |
This is the const version of leftCols(Index). | |
template<int N> | |
NColsBlockXpr< N >::Type | leftCols (Index n=N) |
template<int N> | |
ConstNColsBlockXpr< N >::Type | leftCols (Index n=N) const |
This is the const version of leftCols<int>(). | |
internal::traits< Derived >::Scalar | maxCoeff () const |
template<typename IndexType > | |
internal::traits< Derived >::Scalar | maxCoeff (IndexType *row, IndexType *col) const |
template<typename IndexType > | |
internal::traits< Derived >::Scalar | maxCoeff (IndexType *index) const |
Scalar | mean () const |
ColsBlockXpr | middleCols (Index startCol, Index numCols) |
ConstColsBlockXpr | middleCols (Index startCol, Index numCols) const |
This is the const version of middleCols(Index,Index). | |
template<int N> | |
NColsBlockXpr< N >::Type | middleCols (Index startCol, Index n=N) |
template<int N> | |
ConstNColsBlockXpr< N >::Type | middleCols (Index startCol, Index n=N) const |
This is the const version of middleCols<int>(). | |
RowsBlockXpr | middleRows (Index startRow, Index n) |
ConstRowsBlockXpr | middleRows (Index startRow, Index n) const |
This is the const version of middleRows(Index,Index). | |
template<int N> | |
NRowsBlockXpr< N >::Type | middleRows (Index startRow, Index n=N) |
template<int N> | |
ConstNRowsBlockXpr< N >::Type | middleRows (Index startRow, Index n=N) const |
This is the const version of middleRows<int>(). | |
internal::traits< Derived >::Scalar | minCoeff () const |
template<typename IndexType > | |
internal::traits< Derived >::Scalar | minCoeff (IndexType *row, IndexType *col) const |
template<typename IndexType > | |
internal::traits< Derived >::Scalar | minCoeff (IndexType *index) const |
const NestByValue< Derived > | nestByValue () const |
Index | nonZeros () const |
CommaInitializer< Derived > | operator<< (const Scalar &s) |
template<typename OtherDerived > | |
CommaInitializer< Derived > | operator<< (const DenseBase< OtherDerived > &other) |
template<typename OtherDerived > | |
Derived & | operator= (const DenseBase< OtherDerived > &other) |
Derived & | operator= (const DenseBase &other) |
template<typename OtherDerived > | |
Derived & | operator= (const EigenBase< OtherDerived > &other) |
Copies the generic expression other into *this. | |
Index | outerSize () const |
Scalar | prod () const |
template<typename Func > | |
internal::traits< Derived >::Scalar | redux (const Func &func) const |
template<int RowFactor, int ColFactor> | |
const Replicate< Derived, RowFactor, ColFactor > | replicate () const |
const Replicate< Derived, Dynamic, Dynamic > | replicate (Index rowFactor, Index colFactor) const |
void | resize (Index newSize) |
void | resize (Index rows, Index cols) |
ReverseReturnType | reverse () |
ConstReverseReturnType | reverse () const |
void | reverseInPlace () |
ColsBlockXpr | rightCols (Index n) |
ConstColsBlockXpr | rightCols (Index n) const |
This is the const version of rightCols(Index). | |
template<int N> | |
NColsBlockXpr< N >::Type | rightCols (Index n=N) |
template<int N> | |
ConstNColsBlockXpr< N >::Type | rightCols (Index n=N) const |
This is the const version of rightCols<int>(). | |
RowXpr | row (Index i) |
ConstRowXpr | row (Index i) const |
This is the const version of row(). */. | |
ConstRowwiseReturnType | rowwise () const |
RowwiseReturnType | rowwise () |
SegmentReturnType | segment (Index start, Index n) |
ConstSegmentReturnType | segment (Index start, Index n) const |
This is the const version of segment(Index,Index). | |
template<int N> | |
FixedSegmentReturnType< N >::Type | segment (Index start, Index n=N) |
template<int N> | |
ConstFixedSegmentReturnType< N > ::Type | segment (Index start, Index n=N) const |
This is the const version of segment<int>(Index). | |
template<typename ThenDerived , typename ElseDerived > | |
const Select< Derived, ThenDerived, ElseDerived > | select (const DenseBase< ThenDerived > &thenMatrix, const DenseBase< ElseDerived > &elseMatrix) const |
template<typename ThenDerived > | |
const Select< Derived, ThenDerived, typename ThenDerived::ConstantReturnType > | select (const DenseBase< ThenDerived > &thenMatrix, const typename ThenDerived::Scalar &elseScalar) const |
template<typename ElseDerived > | |
const Select< Derived, typename ElseDerived::ConstantReturnType, ElseDerived > | select (const typename ElseDerived::Scalar &thenScalar, const DenseBase< ElseDerived > &elseMatrix) const |
Derived & | setConstant (const Scalar &value) |
Derived & | setLinSpaced (Index size, const Scalar &low, const Scalar &high) |
Sets a linearly spaced vector. | |
Derived & | setLinSpaced (const Scalar &low, const Scalar &high) |
Sets a linearly spaced vector. | |
Derived & | setOnes () |
Derived & | setRandom () |
Derived & | setZero () |
Scalar | sum () const |
template<typename OtherDerived > | |
void | swap (const DenseBase< OtherDerived > &other) |
template<typename OtherDerived > | |
void | swap (PlainObjectBase< OtherDerived > &other) |
SegmentReturnType | tail (Index n) |
ConstSegmentReturnType | tail (Index n) const |
This is the const version of tail(Index). | |
template<int N> | |
FixedSegmentReturnType< N >::Type | tail (Index n=N) |
template<int N> | |
ConstFixedSegmentReturnType< N > ::Type | tail (Index n=N) const |
This is the const version of tail<int>. | |
BlockXpr | topLeftCorner (Index cRows, Index cCols) |
const ConstBlockXpr | topLeftCorner (Index cRows, Index cCols) const |
This is the const version of topLeftCorner(Index, Index). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | topLeftCorner () |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | topLeftCorner () const |
This is the const version of topLeftCorner<int, int>(). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | topLeftCorner (Index cRows, Index cCols) |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | topLeftCorner (Index cRows, Index cCols) const |
This is the const version of topLeftCorner<int, int>(Index, Index). | |
BlockXpr | topRightCorner (Index cRows, Index cCols) |
const ConstBlockXpr | topRightCorner (Index cRows, Index cCols) const |
This is the const version of topRightCorner(Index, Index). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | topRightCorner () |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | topRightCorner () const |
This is the const version of topRightCorner<int, int>(). | |
template<int CRows, int CCols> | |
FixedBlockXpr< CRows, CCols >::Type | topRightCorner (Index cRows, Index cCols) |
template<int CRows, int CCols> | |
const ConstFixedBlockXpr < CRows, CCols >::Type | topRightCorner (Index cRows, Index cCols) const |
This is the const version of topRightCorner<int, int>(Index, Index). | |
RowsBlockXpr | topRows (Index n) |
ConstRowsBlockXpr | topRows (Index n) const |
This is the const version of topRows(Index). | |
template<int N> | |
NRowsBlockXpr< N >::Type | topRows (Index n=N) |
template<int N> | |
ConstNRowsBlockXpr< N >::Type | topRows (Index n=N) const |
This is the const version of topRows<int>(). | |
TransposeReturnType | transpose () |
ConstTransposeReturnType | transpose () const |
void | transposeInPlace () |
CoeffReturnType | value () const |
template<typename Visitor > | |
void | visit (Visitor &func) const |
Static Public Member Functions | |
static const ConstantReturnType | Constant (Index rows, Index cols, const Scalar &value) |
static const ConstantReturnType | Constant (Index size, const Scalar &value) |
static const ConstantReturnType | Constant (const Scalar &value) |
static const SequentialLinSpacedReturnType | LinSpaced (Sequential_t, Index size, const Scalar &low, const Scalar &high) |
static const RandomAccessLinSpacedReturnType | LinSpaced (Index size, const Scalar &low, const Scalar &high) |
Sets a linearly spaced vector. | |
static const SequentialLinSpacedReturnType | LinSpaced (Sequential_t, const Scalar &low, const Scalar &high) |
static const RandomAccessLinSpacedReturnType | LinSpaced (const Scalar &low, const Scalar &high) |
template<typename CustomNullaryOp > | |
static const CwiseNullaryOp < CustomNullaryOp, PlainObject > | NullaryExpr (Index rows, Index cols, const CustomNullaryOp &func) |
template<typename CustomNullaryOp > | |
static const CwiseNullaryOp < CustomNullaryOp, PlainObject > | NullaryExpr (Index size, const CustomNullaryOp &func) |
template<typename CustomNullaryOp > | |
static const CwiseNullaryOp < CustomNullaryOp, PlainObject > | NullaryExpr (const CustomNullaryOp &func) |
static const ConstantReturnType | Ones (Index rows, Index cols) |
static const ConstantReturnType | Ones (Index size) |
static const ConstantReturnType | Ones () |
static const RandomReturnType | Random (Index rows, Index cols) |
static const RandomReturnType | Random (Index size) |
static const RandomReturnType | Random () |
static const ConstantReturnType | Zero (Index rows, Index cols) |
static const ConstantReturnType | Zero (Index size) |
static const ConstantReturnType | Zero () |
Protected Member Functions | |
DenseBase () | |
Related Functions | |
(Note that these are not member functions.) | |
template<typename Derived > | |
std::ostream & | operator<< (std::ostream &s, const DenseBase< Derived > &m) |
typedef Array<typename internal::traits<Derived>::Scalar, internal::traits<Derived>::RowsAtCompileTime, internal::traits<Derived>::ColsAtCompileTime, AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor), internal::traits<Derived>::MaxRowsAtCompileTime, internal::traits<Derived>::MaxColsAtCompileTime > Eigen::DenseBase< Derived >::PlainArray |
The plain array type corresponding to this expression.
typedef Matrix<typename internal::traits<Derived>::Scalar, internal::traits<Derived>::RowsAtCompileTime, internal::traits<Derived>::ColsAtCompileTime, AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor), internal::traits<Derived>::MaxRowsAtCompileTime, internal::traits<Derived>::MaxColsAtCompileTime > Eigen::DenseBase< Derived >::PlainMatrix |
The plain matrix type corresponding to this expression.
typedef internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value, PlainMatrix, PlainArray>::type Eigen::DenseBase< Derived >::PlainObject |
The plain matrix or array 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 in Eigen::Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >, Eigen::MatrixBase< Derived >, Eigen::MatrixBase< MatrixWrapper< ExpressionType > >, Eigen::MatrixBase< Homogeneous< MatrixType, _Direction > >, Eigen::MatrixBase< Solve< Decomposition, RhsType > >, and Eigen::Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >.
typedef internal::traits<Derived>::Scalar Eigen::DenseBase< Derived >::Scalar |
The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
Reimplemented from Eigen::DenseCoeffsBase< Derived, DirectWriteAccessors >.
typedef internal::traits<Derived>::StorageIndex Eigen::DenseBase< Derived >::StorageIndex |
The type used to store indices.
This typedef is relevant for types that store multiple indices such as PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
typedef Scalar Eigen::DenseBase< Derived >::value_type |
The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
It is an alias for the Scalar type
anonymous enum |
RowsAtCompileTime |
The number of rows at compile-time. This is just a copy of the value provided by the Derived type. If a value is not known at compile-time, it is set to the Dynamic constant. |
ColsAtCompileTime |
The number of columns at compile-time. This is just a copy of the value provided by the Derived type. If a value is not known at compile-time, it is set to the Dynamic constant. |
SizeAtCompileTime |
This is equal to the number of coefficients, i.e. the number of rows times the number of columns, or to Dynamic if this is not known at compile-time.
|
MaxRowsAtCompileTime |
This value is equal to the maximum possible number of rows that this expression might have. If this expression might have an arbitrarily high number of rows, this value is set to Dynamic. This value is useful to know when evaluating an expression, in order to determine whether it is possible to avoid doing a dynamic memory allocation. |
MaxColsAtCompileTime |
This value is equal to the maximum possible number of columns that this expression might have. If this expression might have an arbitrarily high number of columns, this value is set to Dynamic. This value is useful to know when evaluating an expression, in order to determine whether it is possible to avoid doing a dynamic memory allocation. |
MaxSizeAtCompileTime |
This value is equal to the maximum possible number of coefficients that this expression might have. If this expression might have an arbitrarily high number of coefficients, this value is set to Dynamic. This value is useful to know when evaluating an expression, in order to determine whether it is possible to avoid doing a dynamic memory allocation. |
IsVectorAtCompileTime |
This is set to true if either the number of rows or the number of columns is known at compile-time to be equal to 1. Indeed, in that case, we are dealing with a column-vector (if there is only one column) or with a row-vector (if there is only one row). |
Flags |
This stores expression Flags flags which may or may not be inherited by new expressions constructed from this one. See the list of flags. |
IsRowMajor |
True if this expression has row-major storage order. |
Eigen::DenseBase< Derived >::DenseBase | ( | ) | [inline, protected] |
Default constructor. Do nothing.
bool Eigen::DenseBase< Derived >::all | ( | ) | const [inline] |
Example:
Vector3f boxMin(Vector3f::Zero()), boxMax(Vector3f::Ones()); Vector3f p0 = Vector3f::Random(), p1 = Vector3f::Random().cwiseAbs(); // let's check if p0 and p1 are inside the axis aligned box defined by the corners boxMin,boxMax: cout << "Is (" << p0.transpose() << ") inside the box: " << ((boxMin.array()<p0.array()).all() && (boxMax.array()>p0.array()).all()) << endl; cout << "Is (" << p1.transpose() << ") inside the box: " << ((boxMin.array()<p1.array()).all() && (boxMax.array()>p1.array()).all()) << endl;
Output:
Is ( 0.68 -0.211 0.566) inside the box: 0 Is (0.597 0.823 0.605) inside the box: 1
bool Eigen::DenseBase< Derived >::allFinite | ( | ) | const [inline] |
*this
contains only finite numbers, i.e., no NaN and no +/-INF values.bool Eigen::DenseBase< Derived >::any | ( | ) | const [inline] |
BlockXpr Eigen::DenseBase< Derived >::block | ( | Index | startRow, |
Index | startCol, | ||
Index | blockRows, | ||
Index | blockCols | ||
) | [inline] |
startRow | the first row in the block |
startCol | the first column in the block |
blockRows | the number of rows in the block |
blockCols | the number of columns in the block |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.block(1, 1, 2, 2):" << endl << m.block(1, 1, 2, 2) << endl; m.block(1, 1, 2, 2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.block(1, 1, 2, 2): -6 1 -3 0 Now the matrix m is: 7 9 -5 -3 -2 0 0 0 6 0 0 9 6 6 3 9
FixedBlockXpr<NRows,NCols>::Type Eigen::DenseBase< Derived >::block | ( | Index | startRow, |
Index | startCol | ||
) | [inline] |
The template parameters NRows and NCols are the number of rows and columns in the block.
startRow | the first row in the block |
startCol | the first column in the block |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.block<2,2>(1,1):" << endl << m.block<2,2>(1,1) << endl; m.block<2,2>(1,1).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.block<2,2>(1,1): -6 1 -3 0 Now the matrix m is: 7 9 -5 -3 -2 0 0 0 6 0 0 9 6 6 3 9
m.template block<3,3>(1,1);
FixedBlockXpr<NRows,NCols>::Type Eigen::DenseBase< Derived >::block | ( | Index | startRow, |
Index | startCol, | ||
Index | blockRows, | ||
Index | blockCols | ||
) | [inline] |
NRows | number of rows in block as specified at compile-time |
NCols | number of columns in block as specified at compile-time |
startRow | the first row in the block |
startCol | the first column in the block |
blockRows | number of rows in block as specified at run-time |
blockCols | number of columns in block as specified at run-time |
This function is mainly useful for blocks where the number of rows is specified at compile-time and the number of columns is specified at run-time, or vice versa. The compile-time and run-time information should not contradict. In other words, blockRows should equal NRows unless NRows is Dynamic, and the same for the number of columns.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the block:" << endl << m.block<2, Dynamic>(1, 1, 2, 3) << endl; m.block<2, Dynamic>(1, 1, 2, 3).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the block:" << endl << m.block<2, Dynamic>(1, 1, 2, 3) << endl; m.block<2, Dynamic>(1, 1, 2, 3).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
BlockXpr Eigen::DenseBase< Derived >::bottomLeftCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
cRows | the number of rows in the corner |
cCols | the number of columns in the corner |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomLeftCorner(2, 2):" << endl; cout << m.bottomLeftCorner(2, 2) << endl; m.bottomLeftCorner(2, 2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomLeftCorner(2, 2): 6 -3 6 6 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 0 0 0 9 0 0 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::bottomLeftCorner | ( | ) | [inline] |
The template parameters CRows and CCols are the number of rows and columns in the corner.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomLeftCorner<2,2>():" << endl; cout << m.bottomLeftCorner<2,2>() << endl; m.bottomLeftCorner<2,2>().setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomLeftCorner<2,2>(): 6 -3 6 6 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 0 0 0 9 0 0 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::bottomLeftCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
CRows | number of rows in corner as specified at compile-time |
CCols | number of columns in corner as specified at compile-time |
cRows | number of rows in corner as specified at run-time |
cCols | number of columns in corner as specified at run-time |
This function is mainly useful for corners where the number of rows is specified at compile-time and the number of columns is specified at run-time, or vice versa. The compile-time and run-time information should not contradict. In other words, cRows should equal CRows unless CRows is Dynamic, and the same for the number of columns.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomLeftCorner<2,Dynamic>(2,2):" << endl; cout << m.bottomLeftCorner<2,Dynamic>(2,2) << endl; m.bottomLeftCorner<2,Dynamic>(2,2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomLeftCorner<2,Dynamic>(2,2): 6 -3 6 6 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 0 0 0 9 0 0 3 9
BlockXpr Eigen::DenseBase< Derived >::bottomRightCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
cRows | the number of rows in the corner |
cCols | the number of columns in the corner |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomRightCorner(2, 2):" << endl; cout << m.bottomRightCorner(2, 2) << endl; m.bottomRightCorner(2, 2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomRightCorner(2, 2): 0 9 3 9 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 6 -3 0 0 6 6 0 0
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::bottomRightCorner | ( | ) | [inline] |
The template parameters CRows and CCols are the number of rows and columns in the corner.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomRightCorner<2,2>():" << endl; cout << m.bottomRightCorner<2,2>() << endl; m.bottomRightCorner<2,2>().setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomRightCorner<2,2>(): 0 9 3 9 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 6 -3 0 0 6 6 0 0
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::bottomRightCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
CRows | number of rows in corner as specified at compile-time |
CCols | number of columns in corner as specified at compile-time |
cRows | number of rows in corner as specified at run-time |
cCols | number of columns in corner as specified at run-time |
This function is mainly useful for corners where the number of rows is specified at compile-time and the number of columns is specified at run-time, or vice versa. The compile-time and run-time information should not contradict. In other words, cRows should equal CRows unless CRows is Dynamic, and the same for the number of columns.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.bottomRightCorner<2,Dynamic>(2,2):" << endl; cout << m.bottomRightCorner<2,Dynamic>(2,2) << endl; m.bottomRightCorner<2,Dynamic>(2,2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.bottomRightCorner<2,Dynamic>(2,2): 0 9 3 9 Now the matrix m is: 7 9 -5 -3 -2 -6 1 0 6 -3 0 0 6 6 0 0
RowsBlockXpr Eigen::DenseBase< Derived >::bottomRows | ( | Index | n | ) | [inline] |
n | the number of rows in the block |
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.bottomRows(2):" << endl; cout << a.bottomRows(2) << endl; a.bottomRows(2).setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.bottomRows(2): 6 -3 0 9 6 6 3 9 Now the array a is: 7 9 -5 -3 -2 -6 1 0 0 0 0 0 0 0 0 0
NRowsBlockXpr<N>::Type Eigen::DenseBase< Derived >::bottomRows | ( | Index | n = N | ) | [inline] |
N | the number of rows in the block as specified at compile-time |
n | the number of rows in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.bottomRows<2>():" << endl; cout << a.bottomRows<2>() << endl; a.bottomRows<2>().setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.bottomRows<2>(): 6 -3 0 9 6 6 3 9 Now the array a is: 7 9 -5 -3 -2 -6 1 0 0 0 0 0 0 0 0 0
ColXpr Eigen::DenseBase< Derived >::col | ( | Index | i | ) | [inline] |
Example:
Matrix3d m = Matrix3d::Identity(); m.col(1) = Vector3d(4,5,6); cout << m << endl;
Output:
1 4 0 0 5 0 0 6 1
ConstColwiseReturnType Eigen::DenseBase< Derived >::colwise | ( | ) | const [inline] |
Example:
Matrix3d m = Matrix3d::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the sum of each column:" << endl << m.colwise().sum() << endl; cout << "Here is the maximum absolute value of each column:" << endl << m.cwiseAbs().colwise().maxCoeff() << endl;
Output:
Here is the matrix m: 0.68 0.597 -0.33 -0.211 0.823 0.536 0.566 -0.605 -0.444 Here is the sum of each column: 1.04 0.815 -0.238 Here is the maximum absolute value of each column: 0.68 0.823 0.536
DenseBase< Derived >::ColwiseReturnType Eigen::DenseBase< Derived >::colwise | ( | ) | [inline] |
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Constant | ( | Index | rows, |
Index | cols, | ||
const Scalar & | value | ||
) | [inline, static] |
The parameters rows and cols are the number of rows and of columns of the returned matrix. Must be compatible with this DenseBase 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 Zero() should be used instead.
The template parameter CustomNullaryOp is the type of the functor.
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Constant | ( | Index | size, |
const Scalar & | value | ||
) | [inline, static] |
The parameter size is the size of the returned vector. Must be compatible with this DenseBase type.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
This variant is meant to be used for dynamic-size vector types. For fixed-size types, it is redundant to pass size as argument, so Zero() should be used instead.
The template parameter CustomNullaryOp is the type of the functor.
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Constant | ( | const Scalar & | value | ) | [inline, static] |
This variant is only for fixed-size DenseBase types. For dynamic-size types, you need to use the variants taking size arguments.
The template parameter CustomNullaryOp is the type of the functor.
Eigen::Index Eigen::DenseBase< Derived >::count | ( | ) | const [inline] |
EvalReturnType Eigen::DenseBase< Derived >::eval | ( | ) | const [inline] |
Notice that in the case of a plain matrix or vector (not an expression) this function just returns a const reference, in order to avoid a useless copy.
void Eigen::DenseBase< Derived >::fill | ( | const Scalar & | val | ) | [inline] |
Alias for setConstant(): sets all coefficients in this expression to val.
EIGEN_DEPRECATED const Derived& Eigen::DenseBase< Derived >::flagged | ( | ) | const [inline] |
*this
const WithFormat<Derived> Eigen::DenseBase< Derived >::format | ( | const IOFormat & | fmt | ) | const [inline] |
See class IOFormat for some examples.
bool Eigen::DenseBase< Derived >::hasNaN | ( | ) | const [inline] |
*this
contains at least one Not A Number (NaN).SegmentReturnType Eigen::DenseBase< Derived >::head | ( | Index | n | ) | [inline] |
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
n | the number of coefficients in the segment |
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.head(2):" << endl << v.head(2) << endl; v.head(2).setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.head(2): 7 -2 Now the vector v is: 0 0 6 6
FixedSegmentReturnType<N>::Type Eigen::DenseBase< Derived >::head | ( | Index | n = N | ) | [inline] |
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
N | the number of coefficients in the segment as specified at compile-time |
n | the number of coefficients in the segment as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.head(2):" << endl << v.head<2>() << endl; v.head<2>().setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.head(2): 7 -2 Now the vector v is: 0 0 6 6
Index Eigen::DenseBase< Derived >::innerSize | ( | ) | const [inline] |
bool Eigen::DenseBase< Derived >::isApprox | ( | const DenseBase< OtherDerived > & | other, |
const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() |
||
) | const |
true
if *this
is approximately equal to other, within the precision determined by prec.
*this
is approximately equal to the zero matrix or vector. Indeed, isApprox(zero)
returns false unless *this
itself is exactly the zero matrix or vector. If you want to test whether *this
is zero, use internal::isMuchSmallerThan(const RealScalar&, RealScalar) instead.bool Eigen::DenseBase< Derived >::isApproxToConstant | ( | const Scalar & | val, |
const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() |
||
) | const |
bool Eigen::DenseBase< Derived >::isConstant | ( | const Scalar & | val, |
const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() |
||
) | const |
This is just an alias for isApproxToConstant().
bool Eigen::DenseBase< Derived >::isMuchSmallerThan | ( | const typename NumTraits< Scalar >::Real & | other, |
const RealScalar & | prec | ||
) | const |
true
if the norm of *this
is much smaller than other, within the precision determined by prec.
For matrices, the comparison is done using the Hilbert-Schmidt norm. For this reason, the value of the reference scalar other should come from the Hilbert-Schmidt norm of a reference matrix of same dimensions.
bool Eigen::DenseBase< Derived >::isMuchSmallerThan | ( | const DenseBase< OtherDerived > & | other, |
const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() |
||
) | const |
true
if the norm of *this
is much smaller than the norm of other, within the precision determined by prec.
bool Eigen::DenseBase< Derived >::isOnes | ( | const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() | ) | const |
Example:
Matrix3d m = Matrix3d::Ones(); m(0,2) += 1e-4; cout << "Here's the matrix m:" << endl << m << endl; cout << "m.isOnes() returns: " << m.isOnes() << endl; cout << "m.isOnes(1e-3) returns: " << m.isOnes(1e-3) << endl;
Output:
Here's the matrix m: 1 1 1 1 1 1 1 1 1 m.isOnes() returns: 0 m.isOnes(1e-3) returns: 1
bool Eigen::DenseBase< Derived >::isZero | ( | const RealScalar & | prec = NumTraits<Scalar>::dummy_precision() | ) | const |
Example:
Matrix3d m = Matrix3d::Zero(); m(0,2) = 1e-4; cout << "Here's the matrix m:" << endl << m << endl; cout << "m.isZero() returns: " << m.isZero() << endl; cout << "m.isZero(1e-3) returns: " << m.isZero(1e-3) << endl;
Output:
Here's the matrix m: 0 0 0.0001 0 0 0 0 0 0 m.isZero() returns: 0 m.isZero(1e-3) returns: 1
Derived & Eigen::DenseBase< Derived >::lazyAssign | ( | const DenseBase< OtherDerived > & | other | ) | [inline] |
\Ãnternal Copies other into *this without evaluating other.
Reimplemented in Eigen::PlainObjectBase< Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, and Eigen::PlainObjectBase< Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >.
ColsBlockXpr Eigen::DenseBase< Derived >::leftCols | ( | Index | n | ) | [inline] |
n | the number of columns in the block |
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.leftCols(2):" << endl; cout << a.leftCols(2) << endl; a.leftCols(2).setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.leftCols(2): 7 9 -2 -6 6 -3 6 6 Now the array a is: 0 0 -5 -3 0 0 1 0 0 0 0 9 0 0 3 9
NColsBlockXpr<N>::Type Eigen::DenseBase< Derived >::leftCols | ( | Index | n = N | ) | [inline] |
N | the number of columns in the block as specified at compile-time |
n | the number of columns in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.leftCols<2>():" << endl; cout << a.leftCols<2>() << endl; a.leftCols<2>().setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.leftCols<2>(): 7 9 -2 -6 6 -3 6 6 Now the array a is: 0 0 -5 -3 0 0 1 0 0 0 0 9 0 0 3 9
const DenseBase< Derived >::RandomAccessLinSpacedReturnType Eigen::DenseBase< Derived >::LinSpaced | ( | Sequential_t | , |
Index | size, | ||
const Scalar & | low, | ||
const Scalar & | high | ||
) | [inline, static] |
const DenseBase< Derived >::RandomAccessLinSpacedReturnType Eigen::DenseBase< Derived >::LinSpaced | ( | Index | size, |
const Scalar & | low, | ||
const Scalar & | high | ||
) | [inline, static] |
Sets a linearly spaced vector.
The function generates 'size' equally spaced values in the closed interval [low,high]. When size is set to 1, a vector of length 1 containing 'high' is returned.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
Example:
cout << VectorXi::LinSpaced(4,7,10).transpose() << endl; cout << VectorXd::LinSpaced(5,0.0,1.0).transpose() << endl;
Output:
7 8 9 10 0 0.25 0.5 0.75 1
For integer scalar types, an even spacing is possible if and only if the length of the range, i.e., high-low
is a scalar multiple of size-1
, or if size
is a scalar multiple of the number of values high-low+1
(meaning each value can be repeated the same number of time). If one of these two considions is not satisfied, then high
is lowered to the largest value satisfying one of this constraint. Here are some examples:
Example:
cout << "Even spacing inputs:" << endl; cout << VectorXi::LinSpaced(8,1,4).transpose() << endl; cout << VectorXi::LinSpaced(8,1,8).transpose() << endl; cout << VectorXi::LinSpaced(8,1,15).transpose() << endl; cout << "Uneven spacing inputs:" << endl; cout << VectorXi::LinSpaced(8,1,7).transpose() << endl; cout << VectorXi::LinSpaced(8,1,9).transpose() << endl; cout << VectorXi::LinSpaced(8,1,16).transpose() << endl;
Output:
Even spacing inputs: 1 1 2 2 3 3 4 4 1 2 3 4 5 6 7 8 1 3 5 7 9 11 13 15 Uneven spacing inputs: 1 1 2 2 3 3 4 4 1 2 3 4 5 6 7 8 1 3 5 7 9 11 13 15
const DenseBase< Derived >::RandomAccessLinSpacedReturnType Eigen::DenseBase< Derived >::LinSpaced | ( | Sequential_t | , |
const Scalar & | low, | ||
const Scalar & | high | ||
) | [inline, static] |
const DenseBase< Derived >::RandomAccessLinSpacedReturnType Eigen::DenseBase< Derived >::LinSpaced | ( | const Scalar & | low, |
const Scalar & | high | ||
) | [inline, static] |
Sets a linearly spaced vector.
The function generates 'size' equally spaced values in the closed interval [low,high]. When size is set to 1, a vector of length 1 containing 'high' is returned.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
Example:
cout << VectorXi::LinSpaced(4,7,10).transpose() << endl; cout << VectorXd::LinSpaced(5,0.0,1.0).transpose() << endl;
Output:
7 8 9 10 0 0.25 0.5 0.75 1
For integer scalar types, an even spacing is possible if and only if the length of the range, i.e., high-low
is a scalar multiple of size-1
, or if size
is a scalar multiple of the number of values high-low+1
(meaning each value can be repeated the same number of time). If one of these two considions is not satisfied, then high
is lowered to the largest value satisfying one of this constraint. Here are some examples:
Example:
cout << "Even spacing inputs:" << endl; cout << VectorXi::LinSpaced(8,1,4).transpose() << endl; cout << VectorXi::LinSpaced(8,1,8).transpose() << endl; cout << VectorXi::LinSpaced(8,1,15).transpose() << endl; cout << "Uneven spacing inputs:" << endl; cout << VectorXi::LinSpaced(8,1,7).transpose() << endl; cout << VectorXi::LinSpaced(8,1,9).transpose() << endl; cout << VectorXi::LinSpaced(8,1,16).transpose() << endl;
Output:
Even spacing inputs: 1 1 2 2 3 3 4 4 1 2 3 4 5 6 7 8 1 3 5 7 9 11 13 15 Uneven spacing inputs: 1 1 2 2 3 3 4 4 1 2 3 4 5 6 7 8 1 3 5 7 9 11 13 15
internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::maxCoeff | ( | ) | const [inline] |
*this
. *this
contains NaN. internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::maxCoeff | ( | IndexType * | rowId, |
IndexType * | colId | ||
) | const |
*this
contains NaN.internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::maxCoeff | ( | IndexType * | index | ) | const |
*this
contains NaN.internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::mean | ( | ) | const [inline] |
ColsBlockXpr Eigen::DenseBase< Derived >::middleCols | ( | Index | startCol, |
Index | numCols | ||
) | [inline] |
startCol | the index of the first column in the block |
numCols | the number of columns in the block |
Example:
#include <Eigen/Core> #include <iostream> using namespace Eigen; using namespace std; int main(void) { int const N = 5; MatrixXi A(N,N); A.setRandom(); cout << "A =\n" << A << '\n' << endl; cout << "A(1..3,:) =\n" << A.middleCols(1,3) << endl; return 0; }
Output:
A = 7 -6 0 9 -10 -2 -3 3 3 -5 6 6 -3 5 -8 6 -5 0 -8 6 9 1 9 2 -7 A(1..3,:) = -6 0 9 -3 3 3 6 -3 5 -5 0 -8 1 9 2
NColsBlockXpr<N>::Type Eigen::DenseBase< Derived >::middleCols | ( | Index | startCol, |
Index | n = N |
||
) | [inline] |
N | the number of columns in the block as specified at compile-time |
startCol | the index of the first column in the block |
n | the number of columns in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
#include <Eigen/Core> #include <iostream> using namespace Eigen; using namespace std; int main(void) { int const N = 5; MatrixXi A(N,N); A.setRandom(); cout << "A =\n" << A << '\n' << endl; cout << "A(:,1..3) =\n" << A.middleCols<3>(1) << endl; return 0; }
Output:
A = 7 -6 0 9 -10 -2 -3 3 3 -5 6 6 -3 5 -8 6 -5 0 -8 6 9 1 9 2 -7 A(:,1..3) = -6 0 9 -3 3 3 6 -3 5 -5 0 -8 1 9 2
RowsBlockXpr Eigen::DenseBase< Derived >::middleRows | ( | Index | startRow, |
Index | n | ||
) | [inline] |
startRow | the index of the first row in the block |
n | the number of rows in the block |
Example:
#include <Eigen/Core> #include <iostream> using namespace Eigen; using namespace std; int main(void) { int const N = 5; MatrixXi A(N,N); A.setRandom(); cout << "A =\n" << A << '\n' << endl; cout << "A(2..3,:) =\n" << A.middleRows(2,2) << endl; return 0; }
Output:
A = 7 -6 0 9 -10 -2 -3 3 3 -5 6 6 -3 5 -8 6 -5 0 -8 6 9 1 9 2 -7 A(2..3,:) = 6 6 -3 5 -8 6 -5 0 -8 6
NRowsBlockXpr<N>::Type Eigen::DenseBase< Derived >::middleRows | ( | Index | startRow, |
Index | n = N |
||
) | [inline] |
N | the number of rows in the block as specified at compile-time |
startRow | the index of the first row in the block |
n | the number of rows in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
#include <Eigen/Core> #include <iostream> using namespace Eigen; using namespace std; int main(void) { int const N = 5; MatrixXi A(N,N); A.setRandom(); cout << "A =\n" << A << '\n' << endl; cout << "A(1..3,:) =\n" << A.middleRows<3>(1) << endl; return 0; }
Output:
A = 7 -6 0 9 -10 -2 -3 3 3 -5 6 6 -3 5 -8 6 -5 0 -8 6 9 1 9 2 -7 A(1..3,:) = -2 -3 3 3 -5 6 6 -3 5 -8 6 -5 0 -8 6
internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::minCoeff | ( | ) | const [inline] |
*this
. *this
contains NaN. internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::minCoeff | ( | IndexType * | rowId, |
IndexType * | colId | ||
) | const |
*this
contains NaN.internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::minCoeff | ( | IndexType * | index | ) | const |
*this
contains NaN.const NestByValue< Derived > Eigen::DenseBase< Derived >::nestByValue | ( | ) | const [inline] |
Index Eigen::DenseBase< Derived >::nonZeros | ( | ) | const [inline] |
const CwiseNullaryOp< CustomNullaryOp, typename DenseBase< Derived >::PlainObject > Eigen::DenseBase< Derived >::NullaryExpr | ( | Index | rows, |
Index | cols, | ||
const CustomNullaryOp & | func | ||
) | [inline, static] |
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 Zero() should be used instead.
The template parameter CustomNullaryOp is the type of the functor.
const CwiseNullaryOp< CustomNullaryOp, typename DenseBase< Derived >::PlainObject > Eigen::DenseBase< Derived >::NullaryExpr | ( | Index | size, |
const CustomNullaryOp & | func | ||
) | [inline, static] |
The parameter size is the size of the returned vector. Must be compatible with this MatrixBase type.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
This variant is meant to be used for dynamic-size vector types. For fixed-size types, it is redundant to pass size as argument, so Zero() should be used instead.
The template parameter CustomNullaryOp is the type of the functor.
Here is an example with C++11 random generators:
#include <Eigen/Core> #include <iostream> #include <random> using namespace Eigen; int main() { std::default_random_engine generator; std::poisson_distribution<int> distribution(4.1); auto poisson = [&] () {return distribution(generator);}; RowVectorXi v = RowVectorXi::NullaryExpr(10, poisson ); std::cout << v << "\n"; }
Output:
2 3 1 4 3 4 4 3 2 3
const CwiseNullaryOp< CustomNullaryOp, typename DenseBase< Derived >::PlainObject > Eigen::DenseBase< Derived >::NullaryExpr | ( | const CustomNullaryOp & | func | ) | [inline, static] |
This variant is only for fixed-size DenseBase types. For dynamic-size types, you need to use the variants taking size arguments.
The template parameter CustomNullaryOp is the type of the functor.
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Ones | ( | Index | rows, |
Index | cols | ||
) | [inline, static] |
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 Ones() should be used instead.
Example:
cout << MatrixXi::Ones(2,3) << endl;
Output:
1 1 1 1 1 1
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Ones | ( | Index | newSize | ) | [inline, static] |
The parameter newSize is the size of the returned vector. Must be compatible with this MatrixBase type.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
This variant is meant to be used for dynamic-size vector types. For fixed-size types, it is redundant to pass size as argument, so Ones() should be used instead.
Example:
cout << 6 * RowVectorXi::Ones(4) << endl; cout << VectorXf::Ones(2) << endl;
Output:
6 6 6 6 1 1
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Ones | ( | ) | [inline, static] |
This variant is only for fixed-size MatrixBase types. For dynamic-size types, you need to use the variants taking size arguments.
Example:
cout << Matrix2d::Ones() << endl; cout << 6 * RowVector4i::Ones() << endl;
Output:
1 1 1 1 6 6 6 6
CommaInitializer< Derived > Eigen::DenseBase< Derived >::operator<< | ( | const Scalar & | s | ) | [inline] |
Convenient operator to set the coefficients of a matrix.
The coefficients must be provided in a row major order and exactly match the size of the matrix. Otherwise an assertion is raised.
Example:
Matrix3i m1; m1 << 1, 2, 3, 4, 5, 6, 7, 8, 9; cout << m1 << endl << endl; Matrix3i m2 = Matrix3i::Identity(); m2.block(0,0, 2,2) << 10, 11, 12, 13; cout << m2 << endl << endl; Vector2i v1; v1 << 14, 15; m2 << v1.transpose(), 16, v1, m1.block(1,1,2,2); cout << m2 << endl;
Output:
1 2 3 4 5 6 7 8 9 10 11 0 12 13 0 0 0 1 14 15 16 14 5 6 15 8 9
CommaInitializer< Derived > Eigen::DenseBase< Derived >::operator<< | ( | const DenseBase< OtherDerived > & | other | ) | [inline] |
Derived & Eigen::DenseBase< Derived >::operator= | ( | const DenseBase< OtherDerived > & | other | ) | [inline] |
Copies other into *this.
Reimplemented in Eigen::Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >, Eigen::MatrixBase< Derived >, Eigen::MatrixBase< MatrixWrapper< ExpressionType > >, Eigen::MatrixBase< Homogeneous< MatrixType, _Direction > >, Eigen::MatrixBase< Solve< Decomposition, RhsType > >, and Eigen::Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >.
Derived & Eigen::DenseBase< Derived >::operator= | ( | const DenseBase< Derived > & | other | ) | [inline] |
Special case of the template operator=, in order to prevent the compiler from generating a default operator= (issue hit with g++ 4.1)
Derived & Eigen::DenseBase< Derived >::operator= | ( | const EigenBase< OtherDerived > & | other | ) |
Copies the generic expression other into *this.
The expression must provide a (templated) evalTo(Derived& dst) const function which does the actual job. In practice, this allows any user to write its own special matrix without having to modify MatrixBase
Reimplemented in Eigen::PlainObjectBase< Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::PlainObjectBase< Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >, Eigen::MatrixBase< Derived >, Eigen::MatrixBase< MatrixWrapper< ExpressionType > >, Eigen::MatrixBase< Homogeneous< MatrixType, _Direction > >, Eigen::MatrixBase< Solve< Decomposition, RhsType > >, and Eigen::Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols >.
Index Eigen::DenseBase< Derived >::outerSize | ( | ) | const [inline] |
internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::prod | ( | ) | const [inline] |
Example:
Matrix3d m = Matrix3d::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the product of all the coefficients:" << endl << m.prod() << endl;
Output:
Here is the matrix m: 0.68 0.597 -0.33 -0.211 0.823 0.536 0.566 -0.605 -0.444 Here is the product of all the coefficients: 0.0019
const DenseBase< Derived >::RandomReturnType Eigen::DenseBase< Derived >::Random | ( | Index | rows, |
Index | cols | ||
) | [inline, static] |
Numbers are uniformly spread through their whole definition range for integer types, and in the [-1:1] range for floating point scalar types.
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 Random() should be used instead.
Example:
cout << MatrixXi::Random(2,3) << endl;
Output:
7 6 9 -2 6 -6
This expression has the "evaluate before nesting" flag so that it will be evaluated into a temporary matrix whenever it is nested in a larger expression. This prevents unexpected behavior with expressions involving random matrices.
See DenseBase::NullaryExpr(Index, const CustomNullaryOp&) for an example using C++11 random generators.
const DenseBase< Derived >::RandomReturnType Eigen::DenseBase< Derived >::Random | ( | Index | size | ) | [inline, static] |
Numbers are uniformly spread through their whole definition range for integer types, and in the [-1:1] range for floating point scalar types.
The parameter size is the size of the returned vector. Must be compatible with this MatrixBase type.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
This variant is meant to be used for dynamic-size vector types. For fixed-size types, it is redundant to pass size as argument, so Random() should be used instead.
Example:
cout << VectorXi::Random(2) << endl;
Output:
7 -2
This expression has the "evaluate before nesting" flag so that it will be evaluated into a temporary vector whenever it is nested in a larger expression. This prevents unexpected behavior with expressions involving random matrices.
const DenseBase< Derived >::RandomReturnType Eigen::DenseBase< Derived >::Random | ( | ) | [inline, static] |
Numbers are uniformly spread through their whole definition range for integer types, and in the [-1:1] range for floating point scalar types.
This variant is only for fixed-size MatrixBase types. For dynamic-size types, you need to use the variants taking size arguments.
Example:
cout << 100 * Matrix2i::Random() << endl;
Output:
700 600 -200 600
This expression has the "evaluate before nesting" flag so that it will be evaluated into a temporary matrix whenever it is nested in a larger expression. This prevents unexpected behavior with expressions involving random matrices.
internal::traits<Derived>::Scalar Eigen::DenseBase< Derived >::redux | ( | const Func & | func | ) | const |
The template parameter BinaryOp is the type of the functor func which must be an associative operator. Both current C++98 and C++11 functor styles are handled.
const Replicate< Derived, RowFactor, ColFactor > Eigen::DenseBase< Derived >::replicate | ( | ) | const |
*this
Example:
MatrixXi m = MatrixXi::Random(2,3); cout << "Here is the matrix m:" << endl << m << endl; cout << "m.replicate<3,2>() = ..." << endl; cout << m.replicate<3,2>() << endl;
Output:
Here is the matrix m: 7 6 9 -2 6 -6 m.replicate<3,2>() = ... 7 6 9 7 6 9 -2 6 -6 -2 6 -6 7 6 9 7 6 9 -2 6 -6 -2 6 -6 7 6 9 7 6 9 -2 6 -6 -2 6 -6
const Replicate<Derived, Dynamic, Dynamic> Eigen::DenseBase< Derived >::replicate | ( | Index | rowFactor, |
Index | colFactor | ||
) | const [inline] |
*this
Example:
Vector3i v = Vector3i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "v.replicate(2,5) = ..." << endl; cout << v.replicate(2,5) << endl;
Output:
Here is the vector v: 7 -2 6 v.replicate(2,5) = ... 7 7 7 7 7 -2 -2 -2 -2 -2 6 6 6 6 6 7 7 7 7 7 -2 -2 -2 -2 -2 6 6 6 6 6
void Eigen::DenseBase< Derived >::resize | ( | Index | newSize | ) | [inline] |
Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does nothing else.
Reimplemented in Eigen::PlainObjectBase< Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::PlainObjectBase< Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::MatrixWrapper< ExpressionType >, and Eigen::ArrayWrapper< ExpressionType >.
void Eigen::DenseBase< Derived >::resize | ( | Index | rows, |
Index | cols | ||
) | [inline] |
Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does nothing else.
Reimplemented in Eigen::PlainObjectBase< Array< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::PlainObjectBase< Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >, Eigen::MatrixWrapper< ExpressionType >, and Eigen::ArrayWrapper< ExpressionType >.
DenseBase< Derived >::ReverseReturnType Eigen::DenseBase< Derived >::reverse | ( | ) | [inline] |
Example:
MatrixXi m = MatrixXi::Random(3,4); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the reverse of m:" << endl << m.reverse() << endl; cout << "Here is the coefficient (1,0) in the reverse of m:" << endl << m.reverse()(1,0) << endl; cout << "Let us overwrite this coefficient with the value 4." << endl; m.reverse()(1,0) = 4; cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 6 -3 1 -2 9 6 0 6 -6 -5 3 Here is the reverse of m: 3 -5 -6 6 0 6 9 -2 1 -3 6 7 Here is the coefficient (1,0) in the reverse of m: 0 Let us overwrite this coefficient with the value 4. Now the matrix m is: 7 6 -3 1 -2 9 6 4 6 -6 -5 3
ConstReverseReturnType Eigen::DenseBase< Derived >::reverse | ( | ) | const [inline] |
This is the const version of reverse().
void Eigen::DenseBase< Derived >::reverseInPlace | ( | ) | [inline] |
This is the "in place" version of reverse: it reverses *this
.
In most cases it is probably better to simply use the reversed expression of a matrix. However, when reversing the matrix data itself is really needed, then this "in-place" version is probably the right choice because it provides the following additional benefits:
m = m.reverse().eval();
ColsBlockXpr Eigen::DenseBase< Derived >::rightCols | ( | Index | n | ) | [inline] |
n | the number of columns in the block |
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.rightCols(2):" << endl; cout << a.rightCols(2) << endl; a.rightCols(2).setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.rightCols(2): -5 -3 1 0 0 9 3 9 Now the array a is: 7 9 0 0 -2 -6 0 0 6 -3 0 0 6 6 0 0
NColsBlockXpr<N>::Type Eigen::DenseBase< Derived >::rightCols | ( | Index | n = N | ) | [inline] |
N | the number of columns in the block as specified at compile-time |
n | the number of columns in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.rightCols<2>():" << endl; cout << a.rightCols<2>() << endl; a.rightCols<2>().setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.rightCols<2>(): -5 -3 1 0 0 9 3 9 Now the array a is: 7 9 0 0 -2 -6 0 0 6 -3 0 0 6 6 0 0
RowXpr Eigen::DenseBase< Derived >::row | ( | Index | i | ) | [inline] |
Example:
Matrix3d m = Matrix3d::Identity(); m.row(1) = Vector3d(4,5,6); cout << m << endl;
Output:
1 0 0 4 5 6 0 0 1
ConstRowwiseReturnType Eigen::DenseBase< Derived >::rowwise | ( | ) | const [inline] |
Example:
Matrix3d m = Matrix3d::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the sum of each row:" << endl << m.rowwise().sum() << endl; cout << "Here is the maximum absolute value of each row:" << endl << m.cwiseAbs().rowwise().maxCoeff() << endl;
Output:
Here is the matrix m: 0.68 0.597 -0.33 -0.211 0.823 0.536 0.566 -0.605 -0.444 Here is the sum of each row: 0.948 1.15 -0.483 Here is the maximum absolute value of each row: 0.68 0.823 0.605
DenseBase< Derived >::RowwiseReturnType Eigen::DenseBase< Derived >::rowwise | ( | ) | [inline] |
SegmentReturnType Eigen::DenseBase< Derived >::segment | ( | Index | start, |
Index | n | ||
) | [inline] |
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
start | the first coefficient in the segment |
n | the number of coefficients in the segment |
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.segment(1, 2):" << endl << v.segment(1, 2) << endl; v.segment(1, 2).setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.segment(1, 2): -2 6 Now the vector v is: 7 0 0 6
FixedSegmentReturnType<N>::Type Eigen::DenseBase< Derived >::segment | ( | Index | start, |
Index | n = N |
||
) | [inline] |
*this
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
N | the number of coefficients in the segment as specified at compile-time |
start | the index of the first element in the segment |
n | the number of coefficients in the segment as specified at compile-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.segment<2>(1):" << endl << v.segment<2>(1) << endl; v.segment<2>(2).setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.segment<2>(1): -2 6 Now the vector v is: 7 -2 0 0
const Select< Derived, ThenDerived, ElseDerived > Eigen::DenseBase< Derived >::select | ( | const DenseBase< ThenDerived > & | thenMatrix, |
const DenseBase< ElseDerived > & | elseMatrix | ||
) | const [inline] |
const Select< Derived, ThenDerived, typename ThenDerived::ConstantReturnType > Eigen::DenseBase< Derived >::select | ( | const DenseBase< ThenDerived > & | thenMatrix, |
const typename ThenDerived::Scalar & | elseScalar | ||
) | const [inline] |
Version of DenseBase::select(const DenseBase&, const DenseBase&) with the else expression being a scalar value.
const Select< Derived, typename ElseDerived::ConstantReturnType, ElseDerived > Eigen::DenseBase< Derived >::select | ( | const typename ElseDerived::Scalar & | thenScalar, |
const DenseBase< ElseDerived > & | elseMatrix | ||
) | const [inline] |
Version of DenseBase::select(const DenseBase&, const DenseBase&) with the then expression being a scalar value.
Derived & Eigen::DenseBase< Derived >::setConstant | ( | const Scalar & | val | ) | [inline] |
Sets all coefficients in this expression to value val.
Derived & Eigen::DenseBase< Derived >::setLinSpaced | ( | Index | newSize, |
const Scalar & | low, | ||
const Scalar & | high | ||
) | [inline] |
Sets a linearly spaced vector.
The function generates 'size' equally spaced values in the closed interval [low,high]. When size is set to 1, a vector of length 1 containing 'high' is returned.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
Example:
VectorXf v; v.setLinSpaced(5,0.5f,1.5f); cout << v << endl;
Output:
0.5 0.75 1 1.25 1.5
For integer scalar types, do not miss the explanations on the definition of even spacing .
Derived & Eigen::DenseBase< Derived >::setLinSpaced | ( | const Scalar & | low, |
const Scalar & | high | ||
) | [inline] |
Sets a linearly spaced vector.
The function fills *this
with equally spaced values in the closed interval [low,high]. When size is set to 1, a vector of length 1 containing 'high' is returned.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
For integer scalar types, do not miss the explanations on the definition of even spacing .
Derived & Eigen::DenseBase< Derived >::setOnes | ( | ) | [inline] |
Sets all coefficients in this expression to one.
Example:
Matrix4i m = Matrix4i::Random(); m.row(1).setOnes(); cout << m << endl;
Output:
7 9 -5 -3 1 1 1 1 6 -3 0 9 6 6 3 9
Derived & Eigen::DenseBase< Derived >::setRandom | ( | ) | [inline] |
Sets all coefficients in this expression to random values.
Numbers are uniformly spread through their whole definition range for integer types, and in the [-1:1] range for floating point scalar types.
Example:
Matrix4i m = Matrix4i::Zero(); m.col(1).setRandom(); cout << m << endl;
Output:
0 7 0 0 0 -2 0 0 0 6 0 0 0 6 0 0
Derived & Eigen::DenseBase< Derived >::setZero | ( | ) | [inline] |
Sets all coefficients in this expression to zero.
Example:
Matrix4i m = Matrix4i::Random(); m.row(1).setZero(); cout << m << endl;
Output:
7 9 -5 -3 0 0 0 0 6 -3 0 9 6 6 3 9
internal::traits< Derived >::Scalar Eigen::DenseBase< Derived >::sum | ( | ) | const [inline] |
void Eigen::DenseBase< Derived >::swap | ( | const DenseBase< OtherDerived > & | other | ) | [inline] |
swaps *this with the expression other.
void Eigen::DenseBase< Derived >::swap | ( | PlainObjectBase< OtherDerived > & | other | ) | [inline] |
swaps *this with the matrix or array other.
SegmentReturnType Eigen::DenseBase< Derived >::tail | ( | Index | n | ) | [inline] |
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
n | the number of coefficients in the segment |
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.tail(2):" << endl << v.tail(2) << endl; v.tail(2).setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.tail(2): 6 6 Now the vector v is: 7 -2 0 0
FixedSegmentReturnType<N>::Type Eigen::DenseBase< Derived >::tail | ( | Index | n = N | ) | [inline] |
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
N | the number of coefficients in the segment as specified at compile-time |
n | the number of coefficients in the segment as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; cout << "Here is v.tail(2):" << endl << v.tail<2>() << endl; v.tail<2>().setZero(); cout << "Now the vector v is:" << endl << v << endl;
Output:
Here is the vector v: 7 -2 6 6 Here is v.tail(2): 6 6 Now the vector v is: 7 -2 0 0
BlockXpr Eigen::DenseBase< Derived >::topLeftCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
cRows | the number of rows in the corner |
cCols | the number of columns in the corner |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topLeftCorner(2, 2):" << endl; cout << m.topLeftCorner(2, 2) << endl; m.topLeftCorner(2, 2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topLeftCorner(2, 2): 7 9 -2 -6 Now the matrix m is: 0 0 -5 -3 0 0 1 0 6 -3 0 9 6 6 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::topLeftCorner | ( | ) | [inline] |
The template parameters CRows and CCols are the number of rows and columns in the corner.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topLeftCorner<2,2>():" << endl; cout << m.topLeftCorner<2,2>() << endl; m.topLeftCorner<2,2>().setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topLeftCorner<2,2>(): 7 9 -2 -6 Now the matrix m is: 0 0 -5 -3 0 0 1 0 6 -3 0 9 6 6 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::topLeftCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
CRows | number of rows in corner as specified at compile-time |
CCols | number of columns in corner as specified at compile-time |
cRows | number of rows in corner as specified at run-time |
cCols | number of columns in corner as specified at run-time |
This function is mainly useful for corners where the number of rows is specified at compile-time and the number of columns is specified at run-time, or vice versa. The compile-time and run-time information should not contradict. In other words, cRows should equal CRows unless CRows is Dynamic, and the same for the number of columns.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topLeftCorner<2,Dynamic>(2,2):" << endl; cout << m.topLeftCorner<2,Dynamic>(2,2) << endl; m.topLeftCorner<2,Dynamic>(2,2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topLeftCorner<2,Dynamic>(2,2): 7 9 -2 -6 Now the matrix m is: 0 0 -5 -3 0 0 1 0 6 -3 0 9 6 6 3 9
BlockXpr Eigen::DenseBase< Derived >::topRightCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
cRows | the number of rows in the corner |
cCols | the number of columns in the corner |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topRightCorner(2, 2):" << endl; cout << m.topRightCorner(2, 2) << endl; m.topRightCorner(2, 2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topRightCorner(2, 2): -5 -3 1 0 Now the matrix m is: 7 9 0 0 -2 -6 0 0 6 -3 0 9 6 6 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::topRightCorner | ( | ) | [inline] |
CRows | the number of rows in the corner |
CCols | the number of columns in the corner |
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topRightCorner<2,2>():" << endl; cout << m.topRightCorner<2,2>() << endl; m.topRightCorner<2,2>().setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topRightCorner<2,2>(): -5 -3 1 0 Now the matrix m is: 7 9 0 0 -2 -6 0 0 6 -3 0 9 6 6 3 9
FixedBlockXpr<CRows,CCols>::Type Eigen::DenseBase< Derived >::topRightCorner | ( | Index | cRows, |
Index | cCols | ||
) | [inline] |
CRows | number of rows in corner as specified at compile-time |
CCols | number of columns in corner as specified at compile-time |
cRows | number of rows in corner as specified at run-time |
cCols | number of columns in corner as specified at run-time |
This function is mainly useful for corners where the number of rows is specified at compile-time and the number of columns is specified at run-time, or vice versa. The compile-time and run-time information should not contradict. In other words, cRows should equal CRows unless CRows is Dynamic, and the same for the number of columns.
Example:
Matrix4i m = Matrix4i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is m.topRightCorner<2,Dynamic>(2,2):" << endl; cout << m.topRightCorner<2,Dynamic>(2,2) << endl; m.topRightCorner<2,Dynamic>(2,2).setZero(); cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.topRightCorner<2,Dynamic>(2,2): -5 -3 1 0 Now the matrix m is: 7 9 0 0 -2 -6 0 0 6 -3 0 9 6 6 3 9
RowsBlockXpr Eigen::DenseBase< Derived >::topRows | ( | Index | n | ) | [inline] |
n | the number of rows in the block |
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.topRows(2):" << endl; cout << a.topRows(2) << endl; a.topRows(2).setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.topRows(2): 7 9 -5 -3 -2 -6 1 0 Now the array a is: 0 0 0 0 0 0 0 0 6 -3 0 9 6 6 3 9
NRowsBlockXpr<N>::Type Eigen::DenseBase< Derived >::topRows | ( | Index | n = N | ) | [inline] |
N | the number of rows in the block as specified at compile-time |
n | the number of rows in the block as specified at run-time |
The compile-time and run-time information should not contradict. In other words, n should equal N unless N is Dynamic.
Example:
Array44i a = Array44i::Random(); cout << "Here is the array a:" << endl << a << endl; cout << "Here is a.topRows<2>():" << endl; cout << a.topRows<2>() << endl; a.topRows<2>().setZero(); cout << "Now the array a is:" << endl << a << endl;
Output:
Here is the array a: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is a.topRows<2>(): 7 9 -5 -3 -2 -6 1 0 Now the array a is: 0 0 0 0 0 0 0 0 6 -3 0 9 6 6 3 9
Transpose< Derived > Eigen::DenseBase< Derived >::transpose | ( | ) | [inline] |
Example:
Matrix2i m = Matrix2i::Random(); cout << "Here is the matrix m:" << endl << m << endl; cout << "Here is the transpose of m:" << endl << m.transpose() << endl; cout << "Here is the coefficient (1,0) in the transpose of m:" << endl << m.transpose()(1,0) << endl; cout << "Let us overwrite this coefficient with the value 0." << endl; m.transpose()(1,0) = 0; cout << "Now the matrix m is:" << endl << m << endl;
Output:
Here is the matrix m: 7 6 -2 6 Here is the transpose of m: 7 -2 6 6 Here is the coefficient (1,0) in the transpose of m: 6 Let us overwrite this coefficient with the value 0. Now the matrix m is: 7 0 -2 6
m = m.transpose(); // bug!!! caused by aliasing effect
m.transposeInPlace();
m = m.transpose().eval();
DenseBase< Derived >::ConstTransposeReturnType Eigen::DenseBase< Derived >::transpose | ( | ) | const [inline] |
This is the const version of transpose().
Make sure you read the warning for transpose() !
void Eigen::DenseBase< Derived >::transposeInPlace | ( | ) | [inline] |
This is the "in place" version of transpose(): it replaces *this
by its own transpose. Thus, doing
m.transposeInPlace();
has the same effect on m as doing
m = m.transpose().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 transpose. If you just need the transpose of a matrix, use transpose().
*this
must be a resizable matrix. This excludes (non-square) fixed-size matrices, block-expressions and maps.CoeffReturnType Eigen::DenseBase< Derived >::value | ( | ) | const [inline] |
void Eigen::DenseBase< Derived >::visit | ( | Visitor & | visitor | ) | const |
Applies the visitor visitor to the whole coefficients of the matrix or vector.
The template parameter Visitor is the type of the visitor and provides the following interface:
struct MyVisitor { // called for the first coefficient void init(const Scalar& value, Index i, Index j); // called for all other coefficients void operator() (const Scalar& value, Index i, Index j); };
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Zero | ( | Index | rows, |
Index | cols | ||
) | [inline, static] |
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 Zero() should be used instead.
Example:
cout << MatrixXi::Zero(2,3) << endl;
Output:
0 0 0 0 0 0
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Zero | ( | Index | size | ) | [inline, static] |
The parameter size is the size of the returned vector. Must be compatible with this MatrixBase type.
This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column.
This variant is meant to be used for dynamic-size vector types. For fixed-size types, it is redundant to pass size as argument, so Zero() should be used instead.
Example:
cout << RowVectorXi::Zero(4) << endl; cout << VectorXf::Zero(2) << endl;
Output:
0 0 0 0 0 0
const DenseBase< Derived >::ConstantReturnType Eigen::DenseBase< Derived >::Zero | ( | ) | [inline, static] |
This variant is only for fixed-size MatrixBase types. For dynamic-size types, you need to use the variants taking size arguments.
Example:
cout << Matrix2d::Zero() << endl; cout << RowVector4i::Zero() << endl;
Output:
0 0 0 0 0 0 0 0
std::ostream & operator<< | ( | std::ostream & | s, |
const DenseBase< Derived > & | m | ||
) | [related] |
Outputs the matrix, to the given stream.
If you wish to print the matrix with a format different than the default, use DenseBase::format().
It is also possible to change the default format by defining EIGEN_DEFAULT_IO_FORMAT before including Eigen headers. If not defined, this will automatically be defined to Eigen::IOFormat(), that is the Eigen::IOFormat with default parameters.