Several changes in comments to keep Doxygen happy.

This commit is contained in:
Jitse Niesen 2010-07-25 20:29:07 +01:00
parent 3d9764ee24
commit 1420f8b3a1
10 changed files with 30 additions and 32 deletions

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@ -266,7 +266,7 @@ class Array
#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ #define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \
/** \ingroup arraytypedefs */ \ /** \ingroup arraytypedefs */ \
typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix; \ typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix; \
/** \ingroup matrixtypedefs */ \ /** \ingroup arraytypedefs */ \
typedef Array<Type, Size, 1> Array##SizeSuffix##TypeSuffix; typedef Array<Type, Size, 1> Array##SizeSuffix##TypeSuffix;
#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \ #define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \

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@ -251,7 +251,7 @@ DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const
} }
/** /**
* \copydoc DenseBase<Derived>::LinSpaced(Sequential_t, Index, const Scalar&, const Scalar&) * \copydoc DenseBase::LinSpaced(Sequential_t, Index, const Scalar&, const Scalar&)
* Special version for fixed size types which does not require the size parameter. * Special version for fixed size types which does not require the size parameter.
*/ */
template<typename Derived> template<typename Derived>
@ -284,7 +284,7 @@ DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
} }
/** /**
* \copydoc DenseBase<Derived>::LinSpaced(Index, const Scalar&, const Scalar&) * \copydoc DenseBase::LinSpaced(Index, const Scalar&, const Scalar&)
* Special version for fixed size types which does not require the size parameter. * Special version for fixed size types which does not require the size parameter.
*/ */
template<typename Derived> template<typename Derived>
@ -359,6 +359,7 @@ DenseStorageBase<Derived>::setConstant(Index size, const Scalar& value)
* *
* \param rows the new number of rows * \param rows the new number of rows
* \param cols the new number of columns * \param cols the new number of columns
* \param value the value to which all coefficients are set
* *
* Example: \include Matrix_setConstant_int_int.cpp * Example: \include Matrix_setConstant_int_int.cpp
* Output: \verbinclude Matrix_setConstant_int_int.out * Output: \verbinclude Matrix_setConstant_int_int.out

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@ -45,14 +45,13 @@ template<typename Derived> class DenseBase
#endif // not EIGEN_PARSED_BY_DOXYGEN #endif // not EIGEN_PARSED_BY_DOXYGEN
{ {
public: public:
#ifndef EIGEN_PARSED_BY_DOXYGEN
using ei_special_scalar_op_base<Derived,typename ei_traits<Derived>::Scalar, using ei_special_scalar_op_base<Derived,typename ei_traits<Derived>::Scalar,
typename NumTraits<typename ei_traits<Derived>::Scalar>::Real>::operator*; typename NumTraits<typename ei_traits<Derived>::Scalar>::Real>::operator*;
class InnerIterator; class InnerIterator;
typedef typename ei_traits<Derived>::StorageKind StorageKind; typedef typename ei_traits<Derived>::StorageKind StorageKind;
typedef typename ei_traits<Derived>::Index Index; typedef typename ei_traits<Derived>::Index Index; /**< The type of indices */
typedef typename ei_traits<Derived>::Scalar Scalar; typedef typename ei_traits<Derived>::Scalar Scalar;
typedef typename ei_packet_traits<Scalar>::type PacketScalar; typedef typename ei_packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@ -90,8 +89,6 @@ template<typename Derived> class DenseBase
using Base::colStride; using Base::colStride;
using typename Base::CoeffReturnType; using typename Base::CoeffReturnType;
#endif // not EIGEN_PARSED_BY_DOXYGEN
enum { enum {
RowsAtCompileTime = ei_traits<Derived>::RowsAtCompileTime, RowsAtCompileTime = ei_traits<Derived>::RowsAtCompileTime,

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@ -65,7 +65,10 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
public: public:
typedef TriangularBase<SelfAdjointView> Base; typedef TriangularBase<SelfAdjointView> Base;
/** \brief The type of coefficients in this matrix */
typedef typename ei_traits<SelfAdjointView>::Scalar Scalar; typedef typename ei_traits<SelfAdjointView>::Scalar Scalar;
typedef typename MatrixType::Index Index; typedef typename MatrixType::Index Index;
enum { enum {

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@ -135,7 +135,7 @@ template<typename MatrixType,int _Direction> class Homogeneous
* *
* \return an expression of the equivalent homogeneous vector * \return an expression of the equivalent homogeneous vector
* *
* \vectoronly * \only_for_vectors
* *
* Example: \include MatrixBase_homogeneous.cpp * Example: \include MatrixBase_homogeneous.cpp
* Output: \verbinclude MatrixBase_homogeneous.out * Output: \verbinclude MatrixBase_homogeneous.out

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@ -277,19 +277,6 @@ typedef Quaternion<double> Quaterniond;
* Specialization of Map<Quaternion<Scalar>> * Specialization of Map<Quaternion<Scalar>>
***************************************************************************/ ***************************************************************************/
/** \class Map<Quaternion>
*
*
* \brief Expression of a quaternion from a memory buffer
*
* \param _Scalar the type of the Quaternion coefficients
* \param PacketAccess see class Map
*
* This is a specialization of class Map for Quaternion. This class allows to view
* a 4 scalar memory buffer as an Eigen's Quaternion object.
*
* \sa class Map, class Quaternion, class QuaternionBase
*/
template<typename _Scalar, int _PacketAccess> template<typename _Scalar, int _PacketAccess>
struct ei_traits<Map<Quaternion<_Scalar>, _PacketAccess> >: struct ei_traits<Map<Quaternion<_Scalar>, _PacketAccess> >:
ei_traits<Quaternion<_Scalar> > ei_traits<Quaternion<_Scalar> >
@ -301,6 +288,16 @@ ei_traits<Quaternion<_Scalar> >
}; };
}; };
/** \brief Expression of a quaternion from a memory buffer
*
* \param _Scalar the type of the Quaternion coefficients
* \param PacketAccess see class Map
*
* This is a specialization of class Map for Quaternion. This class allows to view
* a 4 scalar memory buffer as an Eigen's Quaternion object.
*
* \sa class Map, class Quaternion, class QuaternionBase
*/
template<typename _Scalar, int PacketAccess> template<typename _Scalar, int PacketAccess>
class Map<Quaternion<_Scalar>, PacketAccess > class Map<Quaternion<_Scalar>, PacketAccess >
: public QuaternionBase<Map<Quaternion<_Scalar>, PacketAccess> > : public QuaternionBase<Map<Quaternion<_Scalar>, PacketAccess> >

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@ -914,7 +914,7 @@ struct ei_projective_transform_inverse<TransformType, Projective>
* \returns the inverse transformation according to some given knowledge * \returns the inverse transformation according to some given knowledge
* on \c *this. * on \c *this.
* *
* \param traits allows to optimize the inversion process when the transformation * \param hint allows to optimize the inversion process when the transformation
* is known to be not a general transformation. The possible values are: * is known to be not a general transformation. The possible values are:
* - Projective if the transformation is not necessarily affine, i.e., if the * - Projective if the transformation is not necessarily affine, i.e., if the
* last row is not guaranteed to be [0 ... 0 1] * last row is not guaranteed to be [0 ... 0 1]

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@ -87,7 +87,7 @@ Output: \verbinclude Tutorial_AdvancedInitialization_LinSpaced.out
This example shows that objects like the ones returned by LinSpaced() can be assigned to variables (and This example shows that objects like the ones returned by LinSpaced() can be assigned to variables (and
expressions). Eigen defines utility functions like \link DenseBase::setZero() setZero()\endlink, expressions). Eigen defines utility functions like \link DenseBase::setZero() setZero()\endlink,
\link MatrixBase::setIdentity() \endlink and \link DenseBase:setLinSpaced() \endlink to do this \link MatrixBase::setIdentity() \endlink and \link DenseBase::setLinSpaced() \endlink to do this
conveniently. The following example contrasts three ways to construct the matrix conveniently. The following example contrasts three ways to construct the matrix
\f$ J = \bigl[ \begin{smallmatrix} O & I \\ I & O \end{smallmatrix} \bigr] \f$: using static methods and \f$ J = \bigl[ \begin{smallmatrix} O & I \\ I & O \end{smallmatrix} \bigr] \f$: using static methods and
assignment, using static methods and the comma-initializer, or using the setXxx() methods. assignment, using static methods and the comma-initializer, or using the setXxx() methods.

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@ -37,7 +37,7 @@ The \em trace of a matrix, as returned by the function \c trace(), is the sum of
\subsection TutorialReductionsVisitorsBroadcastingReductionsNorm Norm reductions \subsection TutorialReductionsVisitorsBroadcastingReductionsNorm Norm reductions
Eigen also provides reductions to obtain the Euclidean norm or squared norm of a vector with \link MatrixBase::norm() norm() \endlink and \link Matrix::squaredNorm() squaredNorm() \endlink respectively. Eigen also provides reductions to obtain the Euclidean norm or squared norm of a vector with \link MatrixBase::norm() norm() \endlink and \link MatrixBase::squaredNorm() squaredNorm() \endlink respectively.
These operations can also operate on matrices; in that case, they use the Frobenius norm. The following example shows these methods. These operations can also operate on matrices; in that case, they use the Frobenius norm. The following example shows these methods.
<table class="tutorial_code"><tr><td> <table class="tutorial_code"><tr><td>
@ -190,7 +190,7 @@ reductions and partial reductions.
Now that broadcasting, reductions and partial reductions have been introduced, we can dive into a more advanced example that finds Now that broadcasting, reductions and partial reductions have been introduced, we can dive into a more advanced example that finds
the nearest neighbour of a vector <tt>v</tt> within the columns of matrix <tt>m</tt>. The Euclidean distance will be used in this example, the nearest neighbour of a vector <tt>v</tt> within the columns of matrix <tt>m</tt>. The Euclidean distance will be used in this example,
computing the squared Euclidean distance with the partial reduction named \link DenseBase::squaredNorm() squaredNorm() \endlink: computing the squared Euclidean distance with the partial reduction named \link MatrixBase::squaredNorm() squaredNorm() \endlink:
<table class="tutorial_code"><tr><td> <table class="tutorial_code"><tr><td>
Example: \include Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp Example: \include Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp

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@ -457,7 +457,7 @@ mat = 2 7 8
\endcode</td></tr> \endcode</td></tr>
</table> </table>
Special versions of \link DenseBase::minCoeff(int*,int*) minCoeff \endlink and \link DenseBase::maxCoeff(int*,int*) maxCoeff \endlink: Special versions of \link DenseBase::minCoeff(Index*,Index*) minCoeff \endlink and \link DenseBase::maxCoeff(Index*,Index*) maxCoeff \endlink:
<div class="desired_tutorial_width"> <div class="desired_tutorial_width">
\code \code
int i, j; int i, j;
@ -476,8 +476,8 @@ if((array1 < array2).any()) ... // if there exist a pair i,j such that array1(i,
<a href="#" class="top">top</a>\section QuickRef_Blocks Sub-matrices <a href="#" class="top">top</a>\section QuickRef_Blocks Sub-matrices
Read-write access to a \link DenseBase::col(int) column \endlink Read-write access to a \link DenseBase::col(Index) column \endlink
or a \link DenseBase::row(int) row \endlink of a matrix (or array): or a \link DenseBase::row(Index) row \endlink of a matrix (or array):
<div class="desired_tutorial_width"> <div class="desired_tutorial_width">
\code \code
mat1.row(i) = mat2.col(j); mat1.row(i) = mat2.col(j);
@ -501,9 +501,9 @@ Read-write access to sub-vectors:
Read-write access to sub-matrices:</td><td></td><td></td></tr> Read-write access to sub-matrices:</td><td></td><td></td></tr>
<tr> <tr>
<td>\code mat1.block(i,j,rows,cols)\endcode <td>\code mat1.block(i,j,rows,cols)\endcode
\link DenseBase::block(int,int,int,int) (more) \endlink</td> \link DenseBase::block(Index,Index,Index,Index) (more) \endlink</td>
<td>\code mat1.block<rows,cols>(i,j)\endcode <td>\code mat1.block<rows,cols>(i,j)\endcode
\link DenseBase::block(int,int) (more) \endlink</td> \link DenseBase::block(Index,Index) (more) \endlink</td>
<td>the \c rows x \c cols sub-matrix \n starting from position (\c i,\c j)</td></tr> <td>the \c rows x \c cols sub-matrix \n starting from position (\c i,\c j)</td></tr>
<tr><td>\code <tr><td>\code
mat1.topLeftCorner(rows,cols) mat1.topLeftCorner(rows,cols)
@ -547,7 +547,7 @@ Declare a diagonal matrix</td><td>\code
DiagonalMatrix<Scalar,SizeAtCompileTime> diag1(size); DiagonalMatrix<Scalar,SizeAtCompileTime> diag1(size);
diag1.diagonal() = vector;\endcode diag1.diagonal() = vector;\endcode
</td></tr> </td></tr>
<tr><td>Access the \link MatrixBase::diagonal() diagonal \endlink and \link MatrixBase::diagonal(int) super/sub diagonals \endlink of a matrix as a vector (read/write)</td> <tr><td>Access the \link MatrixBase::diagonal() diagonal \endlink and \link MatrixBase::diagonal(Index) super/sub diagonals \endlink of a matrix as a vector (read/write)</td>
<td>\code <td>\code
vec1 = mat1.diagonal(); mat1.diagonal() = vec1; // main diagonal vec1 = mat1.diagonal(); mat1.diagonal() = vec1; // main diagonal
vec1 = mat1.diagonal(+n); mat1.diagonal(+n) = vec1; // n-th super diagonal vec1 = mat1.diagonal(+n); mat1.diagonal(+n) = vec1; // n-th super diagonal