// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008 Gael Guennebaud // Copyright (C) 2009 Benoit Jacob // Copyright (C) 2010 Hauke Heibel // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #ifndef EIGEN_TRANSFORM_H #define EIGEN_TRANSFORM_H namespace Eigen { namespace internal { template struct transform_traits { enum { Dim = Transform::Dim, HDim = Transform::HDim, Mode = Transform::Mode, IsProjective = (int(Mode)==int(Projective)) }; }; template< typename TransformType, typename MatrixType, int Case = transform_traits::IsProjective ? 0 : int(MatrixType::RowsAtCompileTime) == int(transform_traits::HDim) ? 1 : 2, int RhsCols = MatrixType::ColsAtCompileTime> struct transform_right_product_impl; template< typename Other, int Mode, int Options, int Dim, int HDim, int OtherRows=Other::RowsAtCompileTime, int OtherCols=Other::ColsAtCompileTime> struct transform_left_product_impl; template< typename Lhs, typename Rhs, bool AnyProjective = transform_traits::IsProjective || transform_traits::IsProjective> struct transform_transform_product_impl; template< typename Other, int Mode, int Options, int Dim, int HDim, int OtherRows=Other::RowsAtCompileTime, int OtherCols=Other::ColsAtCompileTime> struct transform_construct_from_matrix; template struct transform_take_affine_part; template struct traits > { typedef _Scalar Scalar; typedef Eigen::Index StorageIndex; typedef Dense StorageKind; enum { Dim1 = _Dim==Dynamic ? _Dim : _Dim + 1, RowsAtCompileTime = _Mode==Projective ? Dim1 : _Dim, ColsAtCompileTime = Dim1, MaxRowsAtCompileTime = RowsAtCompileTime, MaxColsAtCompileTime = ColsAtCompileTime, Flags = 0 }; }; template struct transform_make_affine; } // end namespace internal /** \geometry_module \ingroup Geometry_Module * * \class Transform * * \brief Represents an homogeneous transformation in a N dimensional space * * \tparam _Scalar the scalar type, i.e., the type of the coefficients * \tparam _Dim the dimension of the space * \tparam _Mode the type of the transformation. Can be: * - #Affine: the transformation is stored as a (Dim+1)^2 matrix, * where the last row is assumed to be [0 ... 0 1]. * - #AffineCompact: the transformation is stored as a (Dim)x(Dim+1) matrix. * - #Projective: the transformation is stored as a (Dim+1)^2 matrix * without any assumption. * \tparam _Options has the same meaning as in class Matrix. It allows to specify DontAlign and/or RowMajor. * These Options are passed directly to the underlying matrix type. * * The homography is internally represented and stored by a matrix which * is available through the matrix() method. To understand the behavior of * this class you have to think a Transform object as its internal * matrix representation. The chosen convention is right multiply: * * \code v' = T * v \endcode * * Therefore, an affine transformation matrix M is shaped like this: * * \f$ \left( \begin{array}{cc} * linear & translation\\ * 0 ... 0 & 1 * \end{array} \right) \f$ * * Note that for a projective transformation the last row can be anything, * and then the interpretation of different parts might be sightly different. * * However, unlike a plain matrix, the Transform class provides many features * simplifying both its assembly and usage. In particular, it can be composed * with any other transformations (Transform,Translation,RotationBase,DiagonalMatrix) * and can be directly used to transform implicit homogeneous vectors. All these * operations are handled via the operator*. For the composition of transformations, * its principle consists to first convert the right/left hand sides of the product * to a compatible (Dim+1)^2 matrix and then perform a pure matrix product. * Of course, internally, operator* tries to perform the minimal number of operations * according to the nature of each terms. Likewise, when applying the transform * to points, the latters are automatically promoted to homogeneous vectors * before doing the matrix product. The conventions to homogeneous representations * are performed as follow: * * \b Translation t (Dim)x(1): * \f$ \left( \begin{array}{cc} * I & t \\ * 0\,...\,0 & 1 * \end{array} \right) \f$ * * \b Rotation R (Dim)x(Dim): * \f$ \left( \begin{array}{cc} * R & 0\\ * 0\,...\,0 & 1 * \end{array} \right) \f$ * * \b Scaling \b DiagonalMatrix S (Dim)x(Dim): * \f$ \left( \begin{array}{cc} * S & 0\\ * 0\,...\,0 & 1 * \end{array} \right) \f$ * * \b Column \b point v (Dim)x(1): * \f$ \left( \begin{array}{c} * v\\ * 1 * \end{array} \right) \f$ * * \b Set \b of \b column \b points V1...Vn (Dim)x(n): * \f$ \left( \begin{array}{ccc} * v_1 & ... & v_n\\ * 1 & ... & 1 * \end{array} \right) \f$ * * The concatenation of a Transform object with any kind of other transformation * always returns a Transform object. * * A little exception to the "as pure matrix product" rule is the case of the * transformation of non homogeneous vectors by an affine transformation. In * that case the last matrix row can be ignored, and the product returns non * homogeneous vectors. * * Since, for instance, a Dim x Dim matrix is interpreted as a linear transformation, * it is not possible to directly transform Dim vectors stored in a Dim x Dim matrix. * The solution is either to use a Dim x Dynamic matrix or explicitly request a * vector transformation by making the vector homogeneous: * \code * m' = T * m.colwise().homogeneous(); * \endcode * Note that there is zero overhead. * * Conversion methods from/to Qt's QMatrix and QTransform are available if the * preprocessor token EIGEN_QT_SUPPORT is defined. * * This class can be extended with the help of the plugin mechanism described on the page * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TRANSFORM_PLUGIN. * * \sa class Matrix, class Quaternion */ template class Transform { public: EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim==Dynamic ? Dynamic : (_Dim+1)*(_Dim+1)) enum { Mode = _Mode, Options = _Options, Dim = _Dim, ///< space dimension in which the transformation holds HDim = _Dim+1, ///< size of a respective homogeneous vector Rows = int(Mode)==(AffineCompact) ? Dim : HDim }; /** the scalar type of the coefficients */ typedef _Scalar Scalar; typedef Eigen::Index StorageIndex; typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3 /** type of the matrix used to represent the transformation */ typedef typename internal::make_proper_matrix_type::type MatrixType; /** constified MatrixType */ typedef const MatrixType ConstMatrixType; /** type of the matrix used to represent the linear part of the transformation */ typedef Matrix LinearMatrixType; /** type of read/write reference to the linear part of the transformation */ typedef Block LinearPart; /** type of read reference to the linear part of the transformation */ typedef const Block ConstLinearPart; /** type of read/write reference to the affine part of the transformation */ typedef typename internal::conditional >::type AffinePart; /** type of read reference to the affine part of the transformation */ typedef typename internal::conditional >::type ConstAffinePart; /** type of a vector */ typedef Matrix VectorType; /** type of a read/write reference to the translation part of the rotation */ typedef Block::Flags & RowMajorBit)> TranslationPart; /** type of a read reference to the translation part of the rotation */ typedef const Block::Flags & RowMajorBit)> ConstTranslationPart; /** corresponding translation type */ typedef Translation TranslationType; // this intermediate enum is needed to avoid an ICE with gcc 3.4 and 4.0 enum { TransformTimeDiagonalMode = ((Mode==int(Isometry))?Affine:int(Mode)) }; /** The return type of the product between a diagonal matrix and a transform */ typedef Transform TransformTimeDiagonalReturnType; protected: MatrixType m_matrix; public: /** Default constructor without initialization of the meaningful coefficients. * If Mode==Affine, then the last row is set to [0 ... 0 1] */ EIGEN_DEVICE_FUNC inline Transform() { check_template_params(); internal::transform_make_affine<(int(Mode)==Affine) ? Affine : AffineCompact>::run(m_matrix); } EIGEN_DEVICE_FUNC inline Transform(const Transform& other) { check_template_params(); m_matrix = other.m_matrix; } EIGEN_DEVICE_FUNC inline explicit Transform(const TranslationType& t) { check_template_params(); *this = t; } EIGEN_DEVICE_FUNC inline explicit Transform(const UniformScaling& s) { check_template_params(); *this = s; } template EIGEN_DEVICE_FUNC inline explicit Transform(const RotationBase& r) { check_template_params(); *this = r; } EIGEN_DEVICE_FUNC inline Transform& operator=(const Transform& other) { m_matrix = other.m_matrix; return *this; } typedef internal::transform_take_affine_part take_affine_part; /** Constructs and initializes a transformation from a Dim^2 or a (Dim+1)^2 matrix. */ template EIGEN_DEVICE_FUNC inline explicit Transform(const EigenBase& other) { EIGEN_STATIC_ASSERT((internal::is_same::value), YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY); check_template_params(); internal::transform_construct_from_matrix::run(this, other.derived()); } /** Set \c *this from a Dim^2 or (Dim+1)^2 matrix. */ template EIGEN_DEVICE_FUNC inline Transform& operator=(const EigenBase& other) { EIGEN_STATIC_ASSERT((internal::is_same::value), YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY); internal::transform_construct_from_matrix::run(this, other.derived()); return *this; } template EIGEN_DEVICE_FUNC inline Transform(const Transform& other) { check_template_params(); // only the options change, we can directly copy the matrices m_matrix = other.matrix(); } template EIGEN_DEVICE_FUNC inline Transform(const Transform& other) { check_template_params(); // prevent conversions as: // Affine | AffineCompact | Isometry = Projective EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(OtherMode==int(Projective), Mode==int(Projective)), YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION) // prevent conversions as: // Isometry = Affine | AffineCompact EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(OtherMode==int(Affine)||OtherMode==int(AffineCompact), Mode!=int(Isometry)), YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION) enum { ModeIsAffineCompact = Mode == int(AffineCompact), OtherModeIsAffineCompact = OtherMode == int(AffineCompact) }; if(EIGEN_CONST_CONDITIONAL(ModeIsAffineCompact == OtherModeIsAffineCompact)) { // We need the block expression because the code is compiled for all // combinations of transformations and will trigger a compile time error // if one tries to assign the matrices directly m_matrix.template block(0,0) = other.matrix().template block(0,0); makeAffine(); } else if(EIGEN_CONST_CONDITIONAL(OtherModeIsAffineCompact)) { typedef typename Transform::MatrixType OtherMatrixType; internal::transform_construct_from_matrix::run(this, other.matrix()); } else { // here we know that Mode == AffineCompact and OtherMode != AffineCompact. // if OtherMode were Projective, the static assert above would already have caught it. // So the only possibility is that OtherMode == Affine linear() = other.linear(); translation() = other.translation(); } } template EIGEN_DEVICE_FUNC Transform(const ReturnByValue& other) { check_template_params(); other.evalTo(*this); } template EIGEN_DEVICE_FUNC Transform& operator=(const ReturnByValue& other) { other.evalTo(*this); return *this; } #ifdef EIGEN_QT_SUPPORT inline Transform(const QMatrix& other); inline Transform& operator=(const QMatrix& other); inline QMatrix toQMatrix(void) const; inline Transform(const QTransform& other); inline Transform& operator=(const QTransform& other); inline QTransform toQTransform(void) const; #endif EIGEN_DEVICE_FUNC Index rows() const { return int(Mode)==int(Projective) ? m_matrix.cols() : (m_matrix.cols()-1); } EIGEN_DEVICE_FUNC Index cols() const { return m_matrix.cols(); } /** shortcut for m_matrix(row,col); * \sa MatrixBase::operator(Index,Index) const */ EIGEN_DEVICE_FUNC inline Scalar operator() (Index row, Index col) const { return m_matrix(row,col); } /** shortcut for m_matrix(row,col); * \sa MatrixBase::operator(Index,Index) */ EIGEN_DEVICE_FUNC inline Scalar& operator() (Index row, Index col) { return m_matrix(row,col); } /** \returns a read-only expression of the transformation matrix */ EIGEN_DEVICE_FUNC inline const MatrixType& matrix() const { return m_matrix; } /** \returns a writable expression of the transformation matrix */ EIGEN_DEVICE_FUNC inline MatrixType& matrix() { return m_matrix; } /** \returns a read-only expression of the linear part of the transformation */ EIGEN_DEVICE_FUNC inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); } /** \returns a writable expression of the linear part of the transformation */ EIGEN_DEVICE_FUNC inline LinearPart linear() { return LinearPart(m_matrix,0,0); } /** \returns a read-only expression of the Dim x HDim affine part of the transformation */ EIGEN_DEVICE_FUNC inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); } /** \returns a writable expression of the Dim x HDim affine part of the transformation */ EIGEN_DEVICE_FUNC inline AffinePart affine() { return take_affine_part::run(m_matrix); } /** \returns a read-only expression of the translation vector of the transformation */ EIGEN_DEVICE_FUNC inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); } /** \returns a writable expression of the translation vector of the transformation */ EIGEN_DEVICE_FUNC inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); } /** \returns an expression of the product between the transform \c *this and a matrix expression \a other. * * The right-hand-side \a other can be either: * \li an homogeneous vector of size Dim+1, * \li a set of homogeneous vectors of size Dim+1 x N, * \li a transformation matrix of size Dim+1 x Dim+1. * * Moreover, if \c *this represents an affine transformation (i.e., Mode!=Projective), then \a other can also be: * \li a point of size Dim (computes: \code this->linear() * other + this->translation()\endcode), * \li a set of N points as a Dim x N matrix (computes: \code (this->linear() * other).colwise() + this->translation()\endcode), * * In all cases, the return type is a matrix or vector of same sizes as the right-hand-side \a other. * * If you want to interpret \a other as a linear or affine transformation, then first convert it to a Transform<> type, * or do your own cooking. * * Finally, if you want to apply Affine transformations to vectors, then explicitly apply the linear part only: * \code * Affine3f A; * Vector3f v1, v2; * v2 = A.linear() * v1; * \endcode * */ // note: this function is defined here because some compilers cannot find the respective declaration template EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::transform_right_product_impl::ResultType operator * (const EigenBase &other) const { return internal::transform_right_product_impl::run(*this,other.derived()); } /** \returns the product expression of a transformation matrix \a a times a transform \a b * * The left hand side \a other can be either: * \li a linear transformation matrix of size Dim x Dim, * \li an affine transformation matrix of size Dim x Dim+1, * \li a general transformation matrix of size Dim+1 x Dim+1. */ template friend EIGEN_DEVICE_FUNC inline const typename internal::transform_left_product_impl::ResultType operator * (const EigenBase &a, const Transform &b) { return internal::transform_left_product_impl::run(a.derived(),b); } /** \returns The product expression of a transform \a a times a diagonal matrix \a b * * The rhs diagonal matrix is interpreted as an affine scaling transformation. The * product results in a Transform of the same type (mode) as the lhs only if the lhs * mode is no isometry. In that case, the returned transform is an affinity. */ template EIGEN_DEVICE_FUNC inline const TransformTimeDiagonalReturnType operator * (const DiagonalBase &b) const { TransformTimeDiagonalReturnType res(*this); res.linearExt() *= b; return res; } /** \returns The product expression of a diagonal matrix \a a times a transform \a b * * The lhs diagonal matrix is interpreted as an affine scaling transformation. The * product results in a Transform of the same type (mode) as the lhs only if the lhs * mode is no isometry. In that case, the returned transform is an affinity. */ template EIGEN_DEVICE_FUNC friend inline TransformTimeDiagonalReturnType operator * (const DiagonalBase &a, const Transform &b) { TransformTimeDiagonalReturnType res; res.linear().noalias() = a*b.linear(); res.translation().noalias() = a*b.translation(); if (EIGEN_CONST_CONDITIONAL(Mode!=int(AffineCompact))) res.matrix().row(Dim) = b.matrix().row(Dim); return res; } template EIGEN_DEVICE_FUNC inline Transform& operator*=(const EigenBase& other) { return *this = *this * other; } /** Concatenates two transformations */ EIGEN_DEVICE_FUNC inline const Transform operator * (const Transform& other) const { return internal::transform_transform_product_impl::run(*this,other); } #if EIGEN_COMP_ICC private: // this intermediate structure permits to workaround a bug in ICC 11: // error: template instantiation resulted in unexpected function type of "Eigen::Transform // (const Eigen::Transform &) const" // (the meaning of a name may have changed since the template declaration -- the type of the template is: // "Eigen::internal::transform_transform_product_impl, // Eigen::Transform, >::ResultType (const Eigen::Transform &) const") // template struct icc_11_workaround { typedef internal::transform_transform_product_impl > ProductType; typedef typename ProductType::ResultType ResultType; }; public: /** Concatenates two different transformations */ template inline typename icc_11_workaround::ResultType operator * (const Transform& other) const { typedef typename icc_11_workaround::ProductType ProductType; return ProductType::run(*this,other); } #else /** Concatenates two different transformations */ template EIGEN_DEVICE_FUNC inline typename internal::transform_transform_product_impl >::ResultType operator * (const Transform& other) const { return internal::transform_transform_product_impl >::run(*this,other); } #endif /** \sa MatrixBase::setIdentity() */ EIGEN_DEVICE_FUNC void setIdentity() { m_matrix.setIdentity(); } /** * \brief Returns an identity transformation. * \todo In the future this function should be returning a Transform expression. */ EIGEN_DEVICE_FUNC static const Transform Identity() { return Transform(MatrixType::Identity()); } template EIGEN_DEVICE_FUNC inline Transform& scale(const MatrixBase &other); template EIGEN_DEVICE_FUNC inline Transform& prescale(const MatrixBase &other); EIGEN_DEVICE_FUNC inline Transform& scale(const Scalar& s); EIGEN_DEVICE_FUNC inline Transform& prescale(const Scalar& s); template EIGEN_DEVICE_FUNC inline Transform& translate(const MatrixBase &other); template EIGEN_DEVICE_FUNC inline Transform& pretranslate(const MatrixBase &other); template EIGEN_DEVICE_FUNC inline Transform& rotate(const RotationType& rotation); template EIGEN_DEVICE_FUNC inline Transform& prerotate(const RotationType& rotation); EIGEN_DEVICE_FUNC Transform& shear(const Scalar& sx, const Scalar& sy); EIGEN_DEVICE_FUNC Transform& preshear(const Scalar& sx, const Scalar& sy); EIGEN_DEVICE_FUNC inline Transform& operator=(const TranslationType& t); EIGEN_DEVICE_FUNC inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); } EIGEN_DEVICE_FUNC inline Transform operator*(const TranslationType& t) const; EIGEN_DEVICE_FUNC inline Transform& operator=(const UniformScaling& t); EIGEN_DEVICE_FUNC inline Transform& operator*=(const UniformScaling& s) { return scale(s.factor()); } EIGEN_DEVICE_FUNC inline TransformTimeDiagonalReturnType operator*(const UniformScaling& s) const { TransformTimeDiagonalReturnType res = *this; res.scale(s.factor()); return res; } EIGEN_DEVICE_FUNC inline Transform& operator*=(const DiagonalMatrix& s) { linearExt() *= s; return *this; } template EIGEN_DEVICE_FUNC inline Transform& operator=(const RotationBase& r); template EIGEN_DEVICE_FUNC inline Transform& operator*=(const RotationBase& r) { return rotate(r.toRotationMatrix()); } template EIGEN_DEVICE_FUNC inline Transform operator*(const RotationBase& r) const; EIGEN_DEVICE_FUNC const LinearMatrixType rotation() const; template EIGEN_DEVICE_FUNC void computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const; template EIGEN_DEVICE_FUNC void computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const; template EIGEN_DEVICE_FUNC Transform& fromPositionOrientationScale(const MatrixBase &position, const OrientationType& orientation, const MatrixBase &scale); EIGEN_DEVICE_FUNC inline Transform inverse(TransformTraits traits = (TransformTraits)Mode) const; /** \returns a const pointer to the column major internal matrix */ EIGEN_DEVICE_FUNC const Scalar* data() const { return m_matrix.data(); } /** \returns a non-const pointer to the column major internal matrix */ EIGEN_DEVICE_FUNC Scalar* data() { return m_matrix.data(); } /** \returns \c *this with scalar type casted to \a NewScalarType * * Note that if \a NewScalarType is equal to the current scalar type of \c *this * then this function smartly returns a const reference to \c *this. */ template EIGEN_DEVICE_FUNC inline typename internal::cast_return_type >::type cast() const { return typename internal::cast_return_type >::type(*this); } /** Copy constructor with scalar type conversion */ template EIGEN_DEVICE_FUNC inline explicit Transform(const Transform& other) { check_template_params(); m_matrix = other.matrix().template cast(); } /** \returns \c true if \c *this is approximately equal to \a other, within the precision * determined by \a prec. * * \sa MatrixBase::isApprox() */ EIGEN_DEVICE_FUNC bool isApprox(const Transform& other, const typename NumTraits::Real& prec = NumTraits::dummy_precision()) const { return m_matrix.isApprox(other.m_matrix, prec); } /** Sets the last row to [0 ... 0 1] */ EIGEN_DEVICE_FUNC void makeAffine() { internal::transform_make_affine::run(m_matrix); } /** \internal * \returns the Dim x Dim linear part if the transformation is affine, * and the HDim x Dim part for projective transformations. */ EIGEN_DEVICE_FUNC inline Block linearExt() { return m_matrix.template block(0,0); } /** \internal * \returns the Dim x Dim linear part if the transformation is affine, * and the HDim x Dim part for projective transformations. */ EIGEN_DEVICE_FUNC inline const Block linearExt() const { return m_matrix.template block(0,0); } /** \internal * \returns the translation part if the transformation is affine, * and the last column for projective transformations. */ EIGEN_DEVICE_FUNC inline Block translationExt() { return m_matrix.template block(0,Dim); } /** \internal * \returns the translation part if the transformation is affine, * and the last column for projective transformations. */ EIGEN_DEVICE_FUNC inline const Block translationExt() const { return m_matrix.template block(0,Dim); } #ifdef EIGEN_TRANSFORM_PLUGIN #include EIGEN_TRANSFORM_PLUGIN #endif protected: #ifndef EIGEN_PARSED_BY_DOXYGEN EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void check_template_params() { EIGEN_STATIC_ASSERT((Options & (DontAlign|RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS) } #endif }; /** \ingroup Geometry_Module */ typedef Transform Isometry2f; /** \ingroup Geometry_Module */ typedef Transform Isometry3f; /** \ingroup Geometry_Module */ typedef Transform Isometry2d; /** \ingroup Geometry_Module */ typedef Transform Isometry3d; /** \ingroup Geometry_Module */ typedef Transform Affine2f; /** \ingroup Geometry_Module */ typedef Transform Affine3f; /** \ingroup Geometry_Module */ typedef Transform Affine2d; /** \ingroup Geometry_Module */ typedef Transform Affine3d; /** \ingroup Geometry_Module */ typedef Transform AffineCompact2f; /** \ingroup Geometry_Module */ typedef Transform AffineCompact3f; /** \ingroup Geometry_Module */ typedef Transform AffineCompact2d; /** \ingroup Geometry_Module */ typedef Transform AffineCompact3d; /** \ingroup Geometry_Module */ typedef Transform Projective2f; /** \ingroup Geometry_Module */ typedef Transform Projective3f; /** \ingroup Geometry_Module */ typedef Transform Projective2d; /** \ingroup Geometry_Module */ typedef Transform Projective3d; /************************** *** Optional QT support *** **************************/ #ifdef EIGEN_QT_SUPPORT /** Initializes \c *this from a QMatrix assuming the dimension is 2. * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template Transform::Transform(const QMatrix& other) { check_template_params(); *this = other; } /** Set \c *this from a QMatrix assuming the dimension is 2. * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template Transform& Transform::operator=(const QMatrix& other) { EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE) if (EIGEN_CONST_CONDITIONAL(Mode == int(AffineCompact))) m_matrix << other.m11(), other.m21(), other.dx(), other.m12(), other.m22(), other.dy(); else m_matrix << other.m11(), other.m21(), other.dx(), other.m12(), other.m22(), other.dy(), 0, 0, 1; return *this; } /** \returns a QMatrix from \c *this assuming the dimension is 2. * * \warning this conversion might loss data if \c *this is not affine * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template QMatrix Transform::toQMatrix(void) const { check_template_params(); EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE) return QMatrix(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(0,2), m_matrix.coeff(1,2)); } /** Initializes \c *this from a QTransform assuming the dimension is 2. * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template Transform::Transform(const QTransform& other) { check_template_params(); *this = other; } /** Set \c *this from a QTransform assuming the dimension is 2. * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template Transform& Transform::operator=(const QTransform& other) { check_template_params(); EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE) if (EIGEN_CONST_CONDITIONAL(Mode == int(AffineCompact))) m_matrix << other.m11(), other.m21(), other.dx(), other.m12(), other.m22(), other.dy(); else m_matrix << other.m11(), other.m21(), other.dx(), other.m12(), other.m22(), other.dy(), other.m13(), other.m23(), other.m33(); return *this; } /** \returns a QTransform from \c *this assuming the dimension is 2. * * This function is available only if the token EIGEN_QT_SUPPORT is defined. */ template QTransform Transform::toQTransform(void) const { EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE) if (EIGEN_CONST_CONDITIONAL(Mode == int(AffineCompact))) return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(0,2), m_matrix.coeff(1,2)); else return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(2,0), m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(2,1), m_matrix.coeff(0,2), m_matrix.coeff(1,2), m_matrix.coeff(2,2)); } #endif /********************* *** Procedural API *** *********************/ /** Applies on the right the non uniform scale transformation represented * by the vector \a other to \c *this and returns a reference to \c *this. * \sa prescale() */ template template EIGEN_DEVICE_FUNC Transform& Transform::scale(const MatrixBase &other) { EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim)) EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) linearExt().noalias() = (linearExt() * other.asDiagonal()); return *this; } /** Applies on the right a uniform scale of a factor \a c to \c *this * and returns a reference to \c *this. * \sa prescale(Scalar) */ template EIGEN_DEVICE_FUNC inline Transform& Transform::scale(const Scalar& s) { EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) linearExt() *= s; return *this; } /** Applies on the left the non uniform scale transformation represented * by the vector \a other to \c *this and returns a reference to \c *this. * \sa scale() */ template template EIGEN_DEVICE_FUNC Transform& Transform::prescale(const MatrixBase &other) { EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim)) EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) affine().noalias() = (other.asDiagonal() * affine()); return *this; } /** Applies on the left a uniform scale of a factor \a c to \c *this * and returns a reference to \c *this. * \sa scale(Scalar) */ template EIGEN_DEVICE_FUNC inline Transform& Transform::prescale(const Scalar& s) { EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) m_matrix.template topRows() *= s; return *this; } /** Applies on the right the translation matrix represented by the vector \a other * to \c *this and returns a reference to \c *this. * \sa pretranslate() */ template template EIGEN_DEVICE_FUNC Transform& Transform::translate(const MatrixBase &other) { EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim)) translationExt() += linearExt() * other; return *this; } /** Applies on the left the translation matrix represented by the vector \a other * to \c *this and returns a reference to \c *this. * \sa translate() */ template template EIGEN_DEVICE_FUNC Transform& Transform::pretranslate(const MatrixBase &other) { EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim)) if(EIGEN_CONST_CONDITIONAL(int(Mode)==int(Projective))) affine() += other * m_matrix.row(Dim); else translation() += other; return *this; } /** Applies on the right the rotation represented by the rotation \a rotation * to \c *this and returns a reference to \c *this. * * The template parameter \a RotationType is the type of the rotation which * must be known by internal::toRotationMatrix<>. * * Natively supported types includes: * - any scalar (2D), * - a Dim x Dim matrix expression, * - a Quaternion (3D), * - a AngleAxis (3D) * * This mechanism is easily extendable to support user types such as Euler angles, * or a pair of Quaternion for 4D rotations. * * \sa rotate(Scalar), class Quaternion, class AngleAxis, prerotate(RotationType) */ template template EIGEN_DEVICE_FUNC Transform& Transform::rotate(const RotationType& rotation) { linearExt() *= internal::toRotationMatrix(rotation); return *this; } /** Applies on the left the rotation represented by the rotation \a rotation * to \c *this and returns a reference to \c *this. * * See rotate() for further details. * * \sa rotate() */ template template EIGEN_DEVICE_FUNC Transform& Transform::prerotate(const RotationType& rotation) { m_matrix.template block(0,0) = internal::toRotationMatrix(rotation) * m_matrix.template block(0,0); return *this; } /** Applies on the right the shear transformation represented * by the vector \a other to \c *this and returns a reference to \c *this. * \warning 2D only. * \sa preshear() */ template EIGEN_DEVICE_FUNC Transform& Transform::shear(const Scalar& sx, const Scalar& sy) { EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) VectorType tmp = linear().col(0)*sy + linear().col(1); linear() << linear().col(0) + linear().col(1)*sx, tmp; return *this; } /** Applies on the left the shear transformation represented * by the vector \a other to \c *this and returns a reference to \c *this. * \warning 2D only. * \sa shear() */ template EIGEN_DEVICE_FUNC Transform& Transform::preshear(const Scalar& sx, const Scalar& sy) { EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS) m_matrix.template block(0,0) = LinearMatrixType(1, sx, sy, 1) * m_matrix.template block(0,0); return *this; } /****************************************************** *** Scaling, Translation and Rotation compatibility *** ******************************************************/ template EIGEN_DEVICE_FUNC inline Transform& Transform::operator=(const TranslationType& t) { linear().setIdentity(); translation() = t.vector(); makeAffine(); return *this; } template EIGEN_DEVICE_FUNC inline Transform Transform::operator*(const TranslationType& t) const { Transform res = *this; res.translate(t.vector()); return res; } template EIGEN_DEVICE_FUNC inline Transform& Transform::operator=(const UniformScaling& s) { m_matrix.setZero(); linear().diagonal().fill(s.factor()); makeAffine(); return *this; } template template EIGEN_DEVICE_FUNC inline Transform& Transform::operator=(const RotationBase& r) { linear() = internal::toRotationMatrix(r); translation().setZero(); makeAffine(); return *this; } template template EIGEN_DEVICE_FUNC inline Transform Transform::operator*(const RotationBase& r) const { Transform res = *this; res.rotate(r.derived()); return res; } /************************ *** Special functions *** ************************/ /** \returns the rotation part of the transformation * * * \svd_module * * \sa computeRotationScaling(), computeScalingRotation(), class SVD */ template EIGEN_DEVICE_FUNC const typename Transform::LinearMatrixType Transform::rotation() const { LinearMatrixType result; computeRotationScaling(&result, (LinearMatrixType*)0); return result; } /** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being * not necessarily positive. * * If either pointer is zero, the corresponding computation is skipped. * * * * \svd_module * * \sa computeScalingRotation(), rotation(), class SVD */ template template EIGEN_DEVICE_FUNC void Transform::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const { JacobiSVD svd(linear(), ComputeFullU | ComputeFullV); Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1 VectorType sv(svd.singularValues()); sv.coeffRef(0) *= x; if(scaling) scaling->lazyAssign(svd.matrixV() * sv.asDiagonal() * svd.matrixV().adjoint()); if(rotation) { LinearMatrixType m(svd.matrixU()); m.col(0) /= x; rotation->lazyAssign(m * svd.matrixV().adjoint()); } } /** decomposes the linear part of the transformation as a product scaling x rotation, the scaling being * not necessarily positive. * * If either pointer is zero, the corresponding computation is skipped. * * * * \svd_module * * \sa computeRotationScaling(), rotation(), class SVD */ template template EIGEN_DEVICE_FUNC void Transform::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const { JacobiSVD svd(linear(), ComputeFullU | ComputeFullV); Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1 VectorType sv(svd.singularValues()); sv.coeffRef(0) *= x; if(scaling) scaling->lazyAssign(svd.matrixU() * sv.asDiagonal() * svd.matrixU().adjoint()); if(rotation) { LinearMatrixType m(svd.matrixU()); m.col(0) /= x; rotation->lazyAssign(m * svd.matrixV().adjoint()); } } /** Convenient method to set \c *this from a position, orientation and scale * of a 3D object. */ template template EIGEN_DEVICE_FUNC Transform& Transform::fromPositionOrientationScale(const MatrixBase &position, const OrientationType& orientation, const MatrixBase &scale) { linear() = internal::toRotationMatrix(orientation); linear() *= scale.asDiagonal(); translation() = position; makeAffine(); return *this; } namespace internal { template struct transform_make_affine { template EIGEN_DEVICE_FUNC static void run(MatrixType &mat) { static const int Dim = MatrixType::ColsAtCompileTime-1; mat.template block<1,Dim>(Dim,0).setZero(); mat.coeffRef(Dim,Dim) = typename MatrixType::Scalar(1); } }; template<> struct transform_make_affine { template EIGEN_DEVICE_FUNC static void run(MatrixType &) { } }; // selector needed to avoid taking the inverse of a 3x4 matrix template struct projective_transform_inverse { EIGEN_DEVICE_FUNC static inline void run(const TransformType&, TransformType&) {} }; template struct projective_transform_inverse { EIGEN_DEVICE_FUNC static inline void run(const TransformType& m, TransformType& res) { res.matrix() = m.matrix().inverse(); } }; } // end namespace internal /** * * \returns the inverse transformation according to some given knowledge * on \c *this. * * \param hint allows to optimize the inversion process when the transformation * is known to be not a general transformation (optional). The possible values are: * - #Projective if the transformation is not necessarily affine, i.e., if the * last row is not guaranteed to be [0 ... 0 1] * - #Affine if the last row can be assumed to be [0 ... 0 1] * - #Isometry if the transformation is only a concatenations of translations * and rotations. * The default is the template class parameter \c Mode. * * \warning unless \a traits is always set to NoShear or NoScaling, this function * requires the generic inverse method of MatrixBase defined in the LU module. If * you forget to include this module, then you will get hard to debug linking errors. * * \sa MatrixBase::inverse() */ template EIGEN_DEVICE_FUNC Transform Transform::inverse(TransformTraits hint) const { Transform res; if (hint == Projective) { internal::projective_transform_inverse::run(*this, res); } else { if (hint == Isometry) { res.matrix().template topLeftCorner() = linear().transpose(); } else if(hint&Affine) { res.matrix().template topLeftCorner() = linear().inverse(); } else { eigen_assert(false && "Invalid transform traits in Transform::Inverse"); } // translation and remaining parts res.matrix().template topRightCorner() = - res.matrix().template topLeftCorner() * translation(); res.makeAffine(); // we do need this, because in the beginning res is uninitialized } return res; } namespace internal { /***************************************************** *** Specializations of take affine part *** *****************************************************/ template struct transform_take_affine_part { typedef typename TransformType::MatrixType MatrixType; typedef typename TransformType::AffinePart AffinePart; typedef typename TransformType::ConstAffinePart ConstAffinePart; static inline AffinePart run(MatrixType& m) { return m.template block(0,0); } static inline ConstAffinePart run(const MatrixType& m) { return m.template block(0,0); } }; template struct transform_take_affine_part > { typedef typename Transform::MatrixType MatrixType; static inline MatrixType& run(MatrixType& m) { return m; } static inline const MatrixType& run(const MatrixType& m) { return m; } }; /***************************************************** *** Specializations of construct from matrix *** *****************************************************/ template struct transform_construct_from_matrix { static inline void run(Transform *transform, const Other& other) { transform->linear() = other; transform->translation().setZero(); transform->makeAffine(); } }; template struct transform_construct_from_matrix { static inline void run(Transform *transform, const Other& other) { transform->affine() = other; transform->makeAffine(); } }; template struct transform_construct_from_matrix { static inline void run(Transform *transform, const Other& other) { transform->matrix() = other; } }; template struct transform_construct_from_matrix { static inline void run(Transform *transform, const Other& other) { transform->matrix() = other.template block(0,0); } }; /********************************************************** *** Specializations of operator* with rhs EigenBase *** **********************************************************/ template struct transform_product_result { enum { Mode = (LhsMode == (int)Projective || RhsMode == (int)Projective ) ? Projective : (LhsMode == (int)Affine || RhsMode == (int)Affine ) ? Affine : (LhsMode == (int)AffineCompact || RhsMode == (int)AffineCompact ) ? AffineCompact : (LhsMode == (int)Isometry || RhsMode == (int)Isometry ) ? Isometry : Projective }; }; template< typename TransformType, typename MatrixType, int RhsCols> struct transform_right_product_impl< TransformType, MatrixType, 0, RhsCols> { typedef typename MatrixType::PlainObject ResultType; static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { return T.matrix() * other; } }; template< typename TransformType, typename MatrixType, int RhsCols> struct transform_right_product_impl< TransformType, MatrixType, 1, RhsCols> { enum { Dim = TransformType::Dim, HDim = TransformType::HDim, OtherRows = MatrixType::RowsAtCompileTime, OtherCols = MatrixType::ColsAtCompileTime }; typedef typename MatrixType::PlainObject ResultType; static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { EIGEN_STATIC_ASSERT(OtherRows==HDim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES); typedef Block TopLeftLhs; ResultType res(other.rows(),other.cols()); TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.affine() * other; res.row(OtherRows-1) = other.row(OtherRows-1); return res; } }; template< typename TransformType, typename MatrixType, int RhsCols> struct transform_right_product_impl< TransformType, MatrixType, 2, RhsCols> { enum { Dim = TransformType::Dim, HDim = TransformType::HDim, OtherRows = MatrixType::RowsAtCompileTime, OtherCols = MatrixType::ColsAtCompileTime }; typedef typename MatrixType::PlainObject ResultType; static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES); typedef Block TopLeftLhs; ResultType res(Replicate(T.translation(),1,other.cols())); TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() += T.linear() * other; return res; } }; template< typename TransformType, typename MatrixType > struct transform_right_product_impl< TransformType, MatrixType, 2, 1> // rhs is a vector of size Dim { typedef typename TransformType::MatrixType TransformMatrix; enum { Dim = TransformType::Dim, HDim = TransformType::HDim, OtherRows = MatrixType::RowsAtCompileTime, WorkingRows = EIGEN_PLAIN_ENUM_MIN(TransformMatrix::RowsAtCompileTime,HDim) }; typedef typename MatrixType::PlainObject ResultType; static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES); Matrix rhs; rhs.template head() = other; rhs[Dim] = typename ResultType::Scalar(1); Matrix res(T.matrix() * rhs); return res.template head(); } }; /********************************************************** *** Specializations of operator* with lhs EigenBase *** **********************************************************/ // generic HDim x HDim matrix * T => Projective template struct transform_left_product_impl { typedef Transform TransformType; typedef typename TransformType::MatrixType MatrixType; typedef Transform ResultType; static ResultType run(const Other& other,const TransformType& tr) { return ResultType(other * tr.matrix()); } }; // generic HDim x HDim matrix * AffineCompact => Projective template struct transform_left_product_impl { typedef Transform TransformType; typedef typename TransformType::MatrixType MatrixType; typedef Transform ResultType; static ResultType run(const Other& other,const TransformType& tr) { ResultType res; res.matrix().noalias() = other.template block(0,0) * tr.matrix(); res.matrix().col(Dim) += other.col(Dim); return res; } }; // affine matrix * T template struct transform_left_product_impl { typedef Transform TransformType; typedef typename TransformType::MatrixType MatrixType; typedef TransformType ResultType; static ResultType run(const Other& other,const TransformType& tr) { ResultType res; res.affine().noalias() = other * tr.matrix(); res.matrix().row(Dim) = tr.matrix().row(Dim); return res; } }; // affine matrix * AffineCompact template struct transform_left_product_impl { typedef Transform TransformType; typedef typename TransformType::MatrixType MatrixType; typedef TransformType ResultType; static ResultType run(const Other& other,const TransformType& tr) { ResultType res; res.matrix().noalias() = other.template block(0,0) * tr.matrix(); res.translation() += other.col(Dim); return res; } }; // linear matrix * T template struct transform_left_product_impl { typedef Transform TransformType; typedef typename TransformType::MatrixType MatrixType; typedef TransformType ResultType; static ResultType run(const Other& other, const TransformType& tr) { TransformType res; if(Mode!=int(AffineCompact)) res.matrix().row(Dim) = tr.matrix().row(Dim); res.matrix().template topRows().noalias() = other * tr.matrix().template topRows(); return res; } }; /********************************************************** *** Specializations of operator* with another Transform *** **********************************************************/ template struct transform_transform_product_impl,Transform,false > { enum { ResultMode = transform_product_result::Mode }; typedef Transform Lhs; typedef Transform Rhs; typedef Transform ResultType; static ResultType run(const Lhs& lhs, const Rhs& rhs) { ResultType res; res.linear() = lhs.linear() * rhs.linear(); res.translation() = lhs.linear() * rhs.translation() + lhs.translation(); res.makeAffine(); return res; } }; template struct transform_transform_product_impl,Transform,true > { typedef Transform Lhs; typedef Transform Rhs; typedef Transform ResultType; static ResultType run(const Lhs& lhs, const Rhs& rhs) { return ResultType( lhs.matrix() * rhs.matrix() ); } }; template struct transform_transform_product_impl,Transform,true > { typedef Transform Lhs; typedef Transform Rhs; typedef Transform ResultType; static ResultType run(const Lhs& lhs, const Rhs& rhs) { ResultType res; res.matrix().template topRows() = lhs.matrix() * rhs.matrix(); res.matrix().row(Dim) = rhs.matrix().row(Dim); return res; } }; template struct transform_transform_product_impl,Transform,true > { typedef Transform Lhs; typedef Transform Rhs; typedef Transform ResultType; static ResultType run(const Lhs& lhs, const Rhs& rhs) { ResultType res(lhs.matrix().template leftCols() * rhs.matrix()); res.matrix().col(Dim) += lhs.matrix().col(Dim); return res; } }; } // end namespace internal } // end namespace Eigen #endif // EIGEN_TRANSFORM_H