diff options
| -rw-r--r-- | Eigen/Core | 1 | ||||
| -rw-r--r-- | Eigen/Sparse | 1 | ||||
| -rw-r--r-- | Eigen/src/Core/ExpressionMaker.h | 61 | ||||
| -rw-r--r-- | Eigen/src/Sparse/SparseExpressionMaker.h | 48 | ||||
| -rw-r--r-- | unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h | 4 | ||||
| -rw-r--r-- | unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h | 85 |
6 files changed, 161 insertions, 39 deletions
diff --git a/Eigen/Core b/Eigen/Core index c8fcb1c09..3dce6422f 100644 --- a/Eigen/Core +++ b/Eigen/Core @@ -200,6 +200,7 @@ namespace Eigen { #include "src/Core/products/TriangularMatrixMatrix.h" #include "src/Core/products/TriangularSolverMatrix.h" #include "src/Core/BandMatrix.h" +#include "src/Core/ExpressionMaker.h" } // namespace Eigen diff --git a/Eigen/Sparse b/Eigen/Sparse index a8888daa3..96bd61419 100644 --- a/Eigen/Sparse +++ b/Eigen/Sparse @@ -110,6 +110,7 @@ namespace Eigen { #include "src/Sparse/SparseLLT.h" #include "src/Sparse/SparseLDLT.h" #include "src/Sparse/SparseLU.h" +#include "src/Sparse/SparseExpressionMaker.h" #ifdef EIGEN_CHOLMOD_SUPPORT # include "src/Sparse/CholmodSupport.h" diff --git a/Eigen/src/Core/ExpressionMaker.h b/Eigen/src/Core/ExpressionMaker.h new file mode 100644 index 000000000..1d265b63c --- /dev/null +++ b/Eigen/src/Core/ExpressionMaker.h @@ -0,0 +1,61 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_EXPRESSIONMAKER_H +#define EIGEN_EXPRESSIONMAKER_H + +// computes the shape of a matrix from its traits flag +template<typename XprType> struct ei_shape_of +{ + enum { ret = ei_traits<XprType>::Flags&SparseBit ? IsSparse : IsDense }; +}; + + +// Since the Sparse module is completely separated from the Core module, there is +// no way to write the type of a generic expression working for both dense and sparse +// matrix. Unless we change the overall design, here is a workaround. +// There is an example in unsuported/Eigen/src/AutoDiff/AutoDiffScalar. + +template<typename XprType, int Shape = ei_shape_of<XprType>::ret> +struct MakeNestByValue +{ + typedef NestByValue<XprType> Type; +}; + +template<typename Func, typename XprType, int Shape = ei_shape_of<XprType>::ret> +struct MakeCwiseUnaryOp +{ + typedef CwiseUnaryOp<Func,XprType> Type; +}; + +template<typename Func, typename A, typename B, int Shape = ei_shape_of<A>::ret> +struct MakeCwiseBinaryOp +{ + typedef CwiseBinaryOp<Func,A,B> Type; +}; + +// TODO complete the list + + +#endif // EIGEN_EXPRESSIONMAKER_H diff --git a/Eigen/src/Sparse/SparseExpressionMaker.h b/Eigen/src/Sparse/SparseExpressionMaker.h new file mode 100644 index 000000000..1fdcbb1f2 --- /dev/null +++ b/Eigen/src/Sparse/SparseExpressionMaker.h @@ -0,0 +1,48 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_SPARSE_EXPRESSIONMAKER_H +#define EIGEN_SPARSE_EXPRESSIONMAKER_H + +template<typename XprType> +struct MakeNestByValue<XprType,IsSparse> +{ + typedef SparseNestByValue<XprType> Type; +}; + +template<typename Func, typename XprType> +struct MakeCwiseUnaryOp<Func,XprType,IsSparse> +{ + typedef SparseCwiseUnaryOp<Func,XprType> Type; +}; + +template<typename Func, typename A, typename B> +struct MakeCwiseBinaryOp<Func,A,B,IsSparse> +{ + typedef SparseCwiseBinaryOp<Func,A,B> Type; +}; + +// TODO complete the list + +#endif // EIGEN_SPARSE_EXPRESSIONMAKER_H diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h b/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h index a5e881487..b3983f8a6 100644 --- a/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h +++ b/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h @@ -50,10 +50,12 @@ public: typedef typename Functor::InputType InputType; typedef typename Functor::ValueType ValueType; typedef typename Functor::JacobianType JacobianType; + typedef typename JacobianType::Scalar Scalar; - typedef Matrix<double,InputsAtCompileTime,1> DerivativeType; + typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType; typedef AutoDiffScalar<DerivativeType> ActiveScalar; + typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput; typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue; diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h index fc5e237ab..2fb733a99 100644 --- a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h +++ b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h @@ -42,9 +42,17 @@ void ei_make_coherent(const A& a, const B&b) /** \class AutoDiffScalar * \brief A scalar type replacement with automatic differentation capability * - * \param DerType the vector type used to store/represent the derivatives (e.g. Vector3f) + * \param _DerType the vector type used to store/represent the derivatives. The base scalar type + * as well as the number of derivatives to compute are determined from this type. + * Typical choices include, e.g., \c Vector4f for 4 derivatives, or \c VectorXf + * if the number of derivatives is not known at compile time, and/or, the number + * of derivatives is large. + * Note that _DerType can also be a reference (e.g., \c VectorXf&) to wrap a + * existing vector into an AutoDiffScalar. + * Finally, _DerType can also be any Eigen compatible expression. * - * This class represents a scalar value while tracking its respective derivatives. + * This class represents a scalar value while tracking its respective derivatives using Eigen's expression + * template mechanism. * * It supports the following list of global math function: * - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos, @@ -56,10 +64,11 @@ void ei_make_coherent(const A& a, const B&b) * while derivatives are computed right away. * */ -template<typename DerType> +template<typename _DerType> class AutoDiffScalar { public: + typedef typename ei_cleantype<_DerType>::type DerType; typedef typename ei_traits<DerType>::Scalar Scalar; inline AutoDiffScalar() {} @@ -108,12 +117,12 @@ class AutoDiffScalar inline const DerType& derivatives() const { return m_derivatives; } inline DerType& derivatives() { return m_derivatives; } - inline const AutoDiffScalar<DerType> operator+(const Scalar& other) const + inline const AutoDiffScalar<DerType&> operator+(const Scalar& other) const { return AutoDiffScalar<DerType>(m_value + other, m_derivatives); } - friend inline const AutoDiffScalar<DerType> operator+(const Scalar& a, const AutoDiffScalar& b) + friend inline const AutoDiffScalar<DerType&> operator+(const Scalar& a, const AutoDiffScalar& b) { return AutoDiffScalar<DerType>(a + b.value(), b.derivatives()); } @@ -125,11 +134,11 @@ class AutoDiffScalar } template<typename OtherDerType> - inline const AutoDiffScalar<CwiseBinaryOp<ei_scalar_sum_op<Scalar>,DerType,OtherDerType> > + inline const AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_sum_op<Scalar>,DerType,typename ei_cleantype<OtherDerType>::type>::Type > operator+(const AutoDiffScalar<OtherDerType>& other) const { ei_make_coherent(m_derivatives, other.derivatives()); - return AutoDiffScalar<CwiseBinaryOp<ei_scalar_sum_op<Scalar>,DerType,OtherDerType> >( + return AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_sum_op<Scalar>,DerType,typename ei_cleantype<OtherDerType>::type>::Type >( m_value + other.value(), m_derivatives + other.derivatives()); } @@ -143,11 +152,11 @@ class AutoDiffScalar } template<typename OtherDerType> - inline const AutoDiffScalar<CwiseBinaryOp<ei_scalar_difference_op<Scalar>, DerType,OtherDerType> > + inline const AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>, DerType,typename ei_cleantype<OtherDerType>::type>::Type > operator-(const AutoDiffScalar<OtherDerType>& other) const { ei_make_coherent(m_derivatives, other.derivatives()); - return AutoDiffScalar<CwiseBinaryOp<ei_scalar_difference_op<Scalar>, DerType,OtherDerType> >( + return AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>, DerType,typename ei_cleantype<OtherDerType>::type>::Type >( m_value - other.value(), m_derivatives - other.derivatives()); } @@ -161,73 +170,73 @@ class AutoDiffScalar } template<typename OtherDerType> - inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_opposite_op<Scalar>, DerType> > + inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, DerType>::Type > operator-() const { - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_opposite_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_opposite_op<Scalar>, DerType>::Type >( -m_value, -m_derivatives); } - inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> > + inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type > operator*(const Scalar& other) const { - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type >( m_value * other, (m_derivatives * other)); } - friend inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> > + friend inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type > operator*(const Scalar& other, const AutoDiffScalar& a) { - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type >( a.value() * other, a.derivatives() * other); } - inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> > + inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type > operator/(const Scalar& other) const { - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type >( m_value / other, (m_derivatives * (Scalar(1)/other))); } - friend inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> > + friend inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type > operator/(const Scalar& other, const AutoDiffScalar& a) { - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type >( other / a.value(), a.derivatives() * (-Scalar(1)/other)); } template<typename OtherDerType> - inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, - NestByValue<CwiseBinaryOp<ei_scalar_difference_op<Scalar>, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherDerType> > > > > > + inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type>::Type, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, typename ei_cleantype<OtherDerType>::type>::Type>::Type >::Type >::Type >::Type > operator/(const AutoDiffScalar<OtherDerType>& other) const { ei_make_coherent(m_derivatives, other.derivatives()); - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, - NestByValue<CwiseBinaryOp<ei_scalar_difference_op<Scalar>, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherDerType> > > > > >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseBinaryOp<ei_scalar_difference_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type>::Type, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, typename ei_cleantype<OtherDerType>::type>::Type>::Type >::Type >::Type >::Type >( m_value / other.value(), ((m_derivatives * other.value()).nestByValue() - (m_value * other.derivatives()).nestByValue()).nestByValue() * (Scalar(1)/(other.value()*other.value()))); } template<typename OtherDerType> - inline const AutoDiffScalar<CwiseBinaryOp<ei_scalar_sum_op<Scalar>, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherDerType> > > > + inline const AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_sum_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type>::Type, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, typename ei_cleantype<OtherDerType>::type>::Type>::Type >::Type > operator*(const AutoDiffScalar<OtherDerType>& other) const { ei_make_coherent(m_derivatives, other.derivatives()); - return AutoDiffScalar<CwiseBinaryOp<ei_scalar_sum_op<Scalar>, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >, - NestByValue<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, OtherDerType> > > >( + return AutoDiffScalar<typename MakeCwiseBinaryOp<ei_scalar_sum_op<Scalar>, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type>::Type, + typename MakeNestByValue<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, typename ei_cleantype<OtherDerType>::type>::Type>::Type >::Type >( m_value * other.value(), (m_derivatives * other.value()).nestByValue() + (m_value * other.derivatives()).nestByValue()); } @@ -299,11 +308,11 @@ struct ei_make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRo #define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \ template<typename DerType> \ - inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::ei_scalar_multiple_op<typename Eigen::ei_traits<DerType>::Scalar>, DerType> > \ + inline const Eigen::AutoDiffScalar<typename Eigen::MakeCwiseUnaryOp<Eigen::ei_scalar_multiple_op<typename Eigen::ei_traits<DerType>::Scalar>, DerType>::Type > \ FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \ using namespace Eigen; \ typedef typename ei_traits<DerType>::Scalar Scalar; \ - typedef AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> > ReturnType; \ + typedef AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type > ReturnType; \ CODE; \ } @@ -330,12 +339,12 @@ namespace std return ReturnType(std::log(x.value),x.derivatives() * (Scalar(1).x.value()));) template<typename DerType> - inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::ei_scalar_multiple_op<typename Eigen::ei_traits<DerType>::Scalar>, DerType> > + inline const Eigen::AutoDiffScalar<typename Eigen::MakeCwiseUnaryOp<Eigen::ei_scalar_multiple_op<typename Eigen::ei_traits<DerType>::Scalar>, DerType>::Type > pow(const Eigen::AutoDiffScalar<DerType>& x, typename Eigen::ei_traits<DerType>::Scalar y) { using namespace Eigen; typedef typename ei_traits<DerType>::Scalar Scalar; - return AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType> >( + return AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, DerType>::Type >( std::pow(x.value(),y), x.derivatives() * (y * std::pow(x.value(),y-1))); } @@ -375,7 +384,7 @@ EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(ei_log, return ReturnType(ei_log(x.value),x.derivatives() * (Scalar(1).x.value()));) template<typename DerType> -inline const AutoDiffScalar<CwiseUnaryOp<ei_scalar_multiple_op<typename ei_traits<DerType>::Scalar>, DerType> > +inline const AutoDiffScalar<typename MakeCwiseUnaryOp<ei_scalar_multiple_op<typename ei_traits<DerType>::Scalar>, DerType>::Type > ei_pow(const AutoDiffScalar<DerType>& x, typename ei_traits<DerType>::Scalar y) { return std::pow(x,y);} |