don't index Eigen

3 files changed, 0 insertions, 1022 deletions

diff --git a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h b/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
deleted file mode 100644
index 33b6c39..0000000
--- a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
+++ /dev/null
@@ -1,108 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// 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_AUTODIFF_JACOBIAN_H
-#define EIGEN_AUTODIFF_JACOBIAN_H
-
-namespace Eigen
-{
-
-template<typename Functor> class AutoDiffJacobian : public Functor
-{
-public:
-  AutoDiffJacobian() : Functor() {}
-  AutoDiffJacobian(const Functor& f) : Functor(f) {}
-
-  // forward constructors
-#if EIGEN_HAS_VARIADIC_TEMPLATES
-  template<typename... T>
-  AutoDiffJacobian(const T& ...Values) : Functor(Values...) {}
-#else
-  template<typename T0>
-  AutoDiffJacobian(const T0& a0) : Functor(a0) {}
-  template<typename T0, typename T1>
-  AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {}
-  template<typename T0, typename T1, typename T2>
-  AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {}
-#endif
-
-  typedef typename Functor::InputType InputType;
-  typedef typename Functor::ValueType ValueType;
-  typedef typename ValueType::Scalar Scalar;
-
-  enum {
-    InputsAtCompileTime = InputType::RowsAtCompileTime,
-    ValuesAtCompileTime = ValueType::RowsAtCompileTime
-  };
-
-  typedef Matrix<Scalar, ValuesAtCompileTime, InputsAtCompileTime> JacobianType;
-  typedef typename JacobianType::Index Index;
-
-  typedef Matrix<Scalar, InputsAtCompileTime, 1> DerivativeType;
-  typedef AutoDiffScalar<DerivativeType> ActiveScalar;
-
-  typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput;
-  typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue;
-
-#if EIGEN_HAS_VARIADIC_TEMPLATES
-  // Some compilers don't accept variadic parameters after a default parameter,
-  // i.e., we can't just write _jac=0 but we need to overload operator():
-  EIGEN_STRONG_INLINE
-  void operator() (const InputType& x, ValueType* v) const
-  {
-      this->operator()(x, v, 0);
-  }
-  template<typename... ParamsType>
-  void operator() (const InputType& x, ValueType* v, JacobianType* _jac,
-                   const ParamsType&... Params) const
-#else
-  void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const
-#endif
-  {
-    eigen_assert(v!=0);
-
-    if (!_jac)
-    {
-#if EIGEN_HAS_VARIADIC_TEMPLATES
-      Functor::operator()(x, v, Params...);
-#else
-      Functor::operator()(x, v);
-#endif
-      return;
-    }
-
-    JacobianType& jac = *_jac;
-
-    ActiveInput ax = x.template cast<ActiveScalar>();
-    ActiveValue av(jac.rows());
-
-    if(InputsAtCompileTime==Dynamic)
-      for (Index j=0; j<jac.rows(); j++)
-        av[j].derivatives().resize(x.rows());
-
-    for (Index i=0; i<jac.cols(); i++)
-      ax[i].derivatives() = DerivativeType::Unit(x.rows(),i);
-
-#if EIGEN_HAS_VARIADIC_TEMPLATES
-    Functor::operator()(ax, &av, Params...);
-#else
-    Functor::operator()(ax, &av);
-#endif
-
-    for (Index i=0; i<jac.rows(); i++)
-    {
-      (*v)[i] = av[i].value();
-      jac.row(i) = av[i].derivatives();
-    }
-  }
-};
-
-}
-
-#endif // EIGEN_AUTODIFF_JACOBIAN_H
diff --git a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h b/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
deleted file mode 100644
index 2f50e99..0000000
--- a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
+++ /dev/null
@@ -1,694 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// 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_AUTODIFF_SCALAR_H
-#define EIGEN_AUTODIFF_SCALAR_H
-
-namespace Eigen {
-
-namespace internal {
-
-template<typename A, typename B>
-struct make_coherent_impl {
-  static void run(A&, B&) {}
-};
-
-// resize a to match b is a.size()==0, and conversely.
-template<typename A, typename B>
-void make_coherent(const A& a, const B&b)
-{
-  make_coherent_impl<A,B>::run(a.const_cast_derived(), b.const_cast_derived());
-}
-
-template<typename _DerType, bool Enable> struct auto_diff_special_op;
-
-} // end namespace internal
-
-template<typename _DerType> class AutoDiffScalar;
-
-template<typename NewDerType>
-inline AutoDiffScalar<NewDerType> MakeAutoDiffScalar(const typename NewDerType::Scalar& value, const NewDerType &der) {
-  return AutoDiffScalar<NewDerType>(value,der);
-}
-
-/** \class AutoDiffScalar
-  * \brief A scalar type replacement with automatic differentation capability
-  *
-  * \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 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,
-  *  - internal::abs, internal::sqrt, numext::pow, internal::exp, internal::log, internal::sin, internal::cos,
-  *  - internal::conj, internal::real, internal::imag, numext::abs2.
-  *
-  * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However,
-  * in that case, the expression template mechanism only occurs at the top Matrix level,
-  * while derivatives are computed right away.
-  *
-  */
-
-template<typename _DerType>
-class AutoDiffScalar
-  : public internal::auto_diff_special_op
-            <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
-                                          typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value>
-{
-  public:
-    typedef internal::auto_diff_special_op
-            <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
-                       typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value> Base;
-    typedef typename internal::remove_all<_DerType>::type DerType;
-    typedef typename internal::traits<DerType>::Scalar Scalar;
-    typedef typename NumTraits<Scalar>::Real Real;
-
-    using Base::operator+;
-    using Base::operator*;
-
-    /** Default constructor without any initialization. */
-    AutoDiffScalar() {}
-
-    /** Constructs an active scalar from its \a value,
-        and initializes the \a nbDer derivatives such that it corresponds to the \a derNumber -th variable */
-    AutoDiffScalar(const Scalar& value, int nbDer, int derNumber)
-      : m_value(value), m_derivatives(DerType::Zero(nbDer))
-    {
-      m_derivatives.coeffRef(derNumber) = Scalar(1);
-    }
-
-    /** Conversion from a scalar constant to an active scalar.
-      * The derivatives are set to zero. */
-    /*explicit*/ AutoDiffScalar(const Real& value)
-      : m_value(value)
-    {
-      if(m_derivatives.size()>0)
-        m_derivatives.setZero();
-    }
-
-    /** Constructs an active scalar from its \a value and derivatives \a der */
-    AutoDiffScalar(const Scalar& value, const DerType& der)
-      : m_value(value), m_derivatives(der)
-    {}
-
-    template<typename OtherDerType>
-    AutoDiffScalar(const AutoDiffScalar<OtherDerType>& other
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    , typename internal::enable_if<
-            internal::is_same<Scalar, typename internal::traits<typename internal::remove_all<OtherDerType>::type>::Scalar>::value
-        &&  internal::is_convertible<OtherDerType,DerType>::value , void*>::type = 0
-#endif
-    )
-      : m_value(other.value()), m_derivatives(other.derivatives())
-    {}
-
-    friend  std::ostream & operator << (std::ostream & s, const AutoDiffScalar& a)
-    {
-      return s << a.value();
-    }
-
-    AutoDiffScalar(const AutoDiffScalar& other)
-      : m_value(other.value()), m_derivatives(other.derivatives())
-    {}
-
-    template<typename OtherDerType>
-    inline AutoDiffScalar& operator=(const AutoDiffScalar<OtherDerType>& other)
-    {
-      m_value = other.value();
-      m_derivatives = other.derivatives();
-      return *this;
-    }
-
-    inline AutoDiffScalar& operator=(const AutoDiffScalar& other)
-    {
-      m_value = other.value();
-      m_derivatives = other.derivatives();
-      return *this;
-    }
-
-    inline AutoDiffScalar& operator=(const Scalar& other)
-    {
-      m_value = other;
-      if(m_derivatives.size()>0)
-        m_derivatives.setZero();
-      return *this;
-    }
-
-//     inline operator const Scalar& () const { return m_value; }
-//     inline operator Scalar& () { return m_value; }
-
-    inline const Scalar& value() const { return m_value; }
-    inline Scalar& value() { return m_value; }
-
-    inline const DerType& derivatives() const { return m_derivatives; }
-    inline DerType& derivatives() { return m_derivatives; }
-
-    inline bool operator< (const Scalar& other) const  { return m_value <  other; }
-    inline bool operator<=(const Scalar& other) const  { return m_value <= other; }
-    inline bool operator> (const Scalar& other) const  { return m_value >  other; }
-    inline bool operator>=(const Scalar& other) const  { return m_value >= other; }
-    inline bool operator==(const Scalar& other) const  { return m_value == other; }
-    inline bool operator!=(const Scalar& other) const  { return m_value != other; }
-
-    friend inline bool operator< (const Scalar& a, const AutoDiffScalar& b) { return a <  b.value(); }
-    friend inline bool operator<=(const Scalar& a, const AutoDiffScalar& b) { return a <= b.value(); }
-    friend inline bool operator> (const Scalar& a, const AutoDiffScalar& b) { return a >  b.value(); }
-    friend inline bool operator>=(const Scalar& a, const AutoDiffScalar& b) { return a >= b.value(); }
-    friend inline bool operator==(const Scalar& a, const AutoDiffScalar& b) { return a == b.value(); }
-    friend inline bool operator!=(const Scalar& a, const AutoDiffScalar& b) { return a != b.value(); }
-
-    template<typename OtherDerType> inline bool operator< (const AutoDiffScalar<OtherDerType>& b) const  { return m_value <  b.value(); }
-    template<typename OtherDerType> inline bool operator<=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value <= b.value(); }
-    template<typename OtherDerType> inline bool operator> (const AutoDiffScalar<OtherDerType>& b) const  { return m_value >  b.value(); }
-    template<typename OtherDerType> inline bool operator>=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value >= b.value(); }
-    template<typename OtherDerType> inline bool operator==(const AutoDiffScalar<OtherDerType>& b) const  { return m_value == b.value(); }
-    template<typename OtherDerType> inline bool operator!=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value != b.value(); }
-
-    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)
-    {
-      return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
-    }
-
-//     inline const AutoDiffScalar<DerType&> operator+(const Real& other) const
-//     {
-//       return AutoDiffScalar<DerType&>(m_value + other, m_derivatives);
-//     }
-
-//     friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar& b)
-//     {
-//       return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
-//     }
-
-    inline AutoDiffScalar& operator+=(const Scalar& other)
-    {
-      value() += other;
-      return *this;
-    }
-
-    template<typename OtherDerType>
-    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> >
-    operator+(const AutoDiffScalar<OtherDerType>& other) const
-    {
-      internal::make_coherent(m_derivatives, other.derivatives());
-      return AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> >(
-        m_value + other.value(),
-        m_derivatives + other.derivatives());
-    }
-
-    template<typename OtherDerType>
-    inline AutoDiffScalar&
-    operator+=(const AutoDiffScalar<OtherDerType>& other)
-    {
-      (*this) = (*this) + other;
-      return *this;
-    }
-
-    inline const AutoDiffScalar<DerType&> operator-(const Scalar& b) const
-    {
-      return AutoDiffScalar<DerType&>(m_value - b, m_derivatives);
-    }
-
-    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
-    operator-(const Scalar& a, const AutoDiffScalar& b)
-    {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
-            (a - b.value(), -b.derivatives());
-    }
-
-    inline AutoDiffScalar& operator-=(const Scalar& other)
-    {
-      value() -= other;
-      return *this;
-    }
-
-    template<typename OtherDerType>
-    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> >
-    operator-(const AutoDiffScalar<OtherDerType>& other) const
-    {
-      internal::make_coherent(m_derivatives, other.derivatives());
-      return AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> >(
-        m_value - other.value(),
-        m_derivatives - other.derivatives());
-    }
-
-    template<typename OtherDerType>
-    inline AutoDiffScalar&
-    operator-=(const AutoDiffScalar<OtherDerType>& other)
-    {
-      *this = *this - other;
-      return *this;
-    }
-
-    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
-    operator-() const
-    {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >(
-        -m_value,
-        -m_derivatives);
-    }
-
-    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
-    operator*(const Scalar& other) const
-    {
-      return MakeAutoDiffScalar(m_value * other, m_derivatives * other);
-    }
-
-    friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
-    operator*(const Scalar& other, const AutoDiffScalar& a)
-    {
-      return MakeAutoDiffScalar(a.value() * other, a.derivatives() * other);
-    }
-
-//     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
-//     operator*(const Real& other) const
-//     {
-//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
-//         m_value * other,
-//         (m_derivatives * other));
-//     }
-//
-//     friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
-//     operator*(const Real& other, const AutoDiffScalar& a)
-//     {
-//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
-//         a.value() * other,
-//         a.derivatives() * other);
-//     }
-
-    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
-    operator/(const Scalar& other) const
-    {
-      return MakeAutoDiffScalar(m_value / other, (m_derivatives * (Scalar(1)/other)));
-    }
-
-    friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
-    operator/(const Scalar& other, const AutoDiffScalar& a)
-    {
-      return MakeAutoDiffScalar(other / a.value(), a.derivatives() * (Scalar(-other) / (a.value()*a.value())));
-    }
-
-//     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
-//     operator/(const Real& other) const
-//     {
-//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
-//         m_value / other,
-//         (m_derivatives * (Real(1)/other)));
-//     }
-//
-//     friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
-//     operator/(const Real& other, const AutoDiffScalar& a)
-//     {
-//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
-//         other / a.value(),
-//         a.derivatives() * (-Real(1)/other));
-//     }
-
-    template<typename OtherDerType>
-    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(
-        CwiseBinaryOp<internal::scalar_difference_op<Scalar> EIGEN_COMMA
-          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) EIGEN_COMMA
-          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) >,Scalar,product) >
-    operator/(const AutoDiffScalar<OtherDerType>& other) const
-    {
-      internal::make_coherent(m_derivatives, other.derivatives());
-      return MakeAutoDiffScalar(
-        m_value / other.value(),
-          ((m_derivatives * other.value()) - (other.derivatives() * m_value))
-        * (Scalar(1)/(other.value()*other.value())));
-    }
-
-    template<typename OtherDerType>
-    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
-        const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product),
-        const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) > >
-    operator*(const AutoDiffScalar<OtherDerType>& other) const
-    {
-      internal::make_coherent(m_derivatives, other.derivatives());
-      return MakeAutoDiffScalar(
-        m_value * other.value(),
-        (m_derivatives * other.value()) + (other.derivatives() * m_value));
-    }
-
-    inline AutoDiffScalar& operator*=(const Scalar& other)
-    {
-      *this = *this * other;
-      return *this;
-    }
-
-    template<typename OtherDerType>
-    inline AutoDiffScalar& operator*=(const AutoDiffScalar<OtherDerType>& other)
-    {
-      *this = *this * other;
-      return *this;
-    }
-
-    inline AutoDiffScalar& operator/=(const Scalar& other)
-    {
-      *this = *this / other;
-      return *this;
-    }
-
-    template<typename OtherDerType>
-    inline AutoDiffScalar& operator/=(const AutoDiffScalar<OtherDerType>& other)
-    {
-      *this = *this / other;
-      return *this;
-    }
-
-  protected:
-    Scalar m_value;
-    DerType m_derivatives;
-
-};
-
-namespace internal {
-
-template<typename _DerType>
-struct auto_diff_special_op<_DerType, true>
-//   : auto_diff_scalar_op<_DerType, typename NumTraits<Scalar>::Real,
-//                            is_same<Scalar,typename NumTraits<Scalar>::Real>::value>
-{
-  typedef typename remove_all<_DerType>::type DerType;
-  typedef typename traits<DerType>::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real Real;
-
-//   typedef auto_diff_scalar_op<_DerType, typename NumTraits<Scalar>::Real,
-//                            is_same<Scalar,typename NumTraits<Scalar>::Real>::value> Base;
-
-//   using Base::operator+;
-//   using Base::operator+=;
-//   using Base::operator-;
-//   using Base::operator-=;
-//   using Base::operator*;
-//   using Base::operator*=;
-
-  const AutoDiffScalar<_DerType>& derived() const { return *static_cast<const AutoDiffScalar<_DerType>*>(this); }
-  AutoDiffScalar<_DerType>& derived() { return *static_cast<AutoDiffScalar<_DerType>*>(this); }
-
-
-  inline const AutoDiffScalar<DerType&> operator+(const Real& other) const
-  {
-    return AutoDiffScalar<DerType&>(derived().value() + other, derived().derivatives());
-  }
-
-  friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar<_DerType>& b)
-  {
-    return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
-  }
-
-  inline AutoDiffScalar<_DerType>& operator+=(const Real& other)
-  {
-    derived().value() += other;
-    return derived();
-  }
-
-
-  inline const AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type >
-  operator*(const Real& other) const
-  {
-    return AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type >(
-      derived().value() * other,
-      derived().derivatives() * other);
-  }
-
-  friend inline const AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type >
-  operator*(const Real& other, const AutoDiffScalar<_DerType>& a)
-  {
-    return AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type >(
-      a.value() * other,
-      a.derivatives() * other);
-  }
-
-  inline AutoDiffScalar<_DerType>& operator*=(const Scalar& other)
-  {
-    *this = *this * other;
-    return derived();
-  }
-};
-
-template<typename _DerType>
-struct auto_diff_special_op<_DerType, false>
-{
-  void operator*() const;
-  void operator-() const;
-  void operator+() const;
-};
-
-template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols, typename B>
-struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>, B> {
-  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
-  static void run(A& a, B& b) {
-    if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0))
-    {
-      a.resize(b.size());
-      a.setZero();
-    }
-  }
-};
-
-template<typename A, typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols>
-struct make_coherent_impl<A, Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
-  typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B;
-  static void run(A& a, B& b) {
-    if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0))
-    {
-      b.resize(a.size());
-      b.setZero();
-    }
-  }
-};
-
-template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols,
-         typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols>
-struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>,
-                             Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
-  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
-  typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B;
-  static void run(A& a, B& b) {
-    if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0))
-    {
-      a.resize(b.size());
-      a.setZero();
-    }
-    else if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0))
-    {
-      b.resize(a.size());
-      b.setZero();
-    }
-  }
-};
-
-} // end namespace internal
-
-template<typename DerType, typename BinOp>
-struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,typename DerType::Scalar,BinOp>
-{
-  typedef AutoDiffScalar<DerType> ReturnType;
-};
-
-template<typename DerType, typename BinOp>
-struct ScalarBinaryOpTraits<typename DerType::Scalar,AutoDiffScalar<DerType>, BinOp>
-{
-  typedef AutoDiffScalar<DerType> ReturnType;
-};
-
-
-// The following is an attempt to let Eigen's known about expression template, but that's more tricky!
-
-// template<typename DerType, typename BinOp>
-// struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,AutoDiffScalar<DerType>, BinOp>
-// {
-//   enum { Defined = 1 };
-//   typedef AutoDiffScalar<typename DerType::PlainObject> ReturnType;
-// };
-//
-// template<typename DerType1,typename DerType2, typename BinOp>
-// struct ScalarBinaryOpTraits<AutoDiffScalar<DerType1>,AutoDiffScalar<DerType2>, BinOp>
-// {
-//   enum { Defined = 1 };//internal::is_same<typename DerType1::Scalar,typename DerType2::Scalar>::value };
-//   typedef AutoDiffScalar<typename DerType1::PlainObject> ReturnType;
-// };
-
-#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
-  template<typename DerType> \
-  inline const Eigen::AutoDiffScalar< \
-  EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename Eigen::internal::remove_all<DerType>::type, typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar, product) > \
-  FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \
-    using namespace Eigen; \
-    typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \
-    EIGEN_UNUSED_VARIABLE(sizeof(Scalar)); \
-    CODE; \
-  }
-
-template<typename DerType>
-inline const AutoDiffScalar<DerType>& conj(const AutoDiffScalar<DerType>& x)  { return x; }
-template<typename DerType>
-inline const AutoDiffScalar<DerType>& real(const AutoDiffScalar<DerType>& x)  { return x; }
-template<typename DerType>
-inline typename DerType::Scalar imag(const AutoDiffScalar<DerType>&)    { return 0.; }
-template<typename DerType, typename T>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const AutoDiffScalar<DerType>& x, const T& y) {
-  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
-  return (x <= y ? ADS(x) : ADS(y));
-}
-template<typename DerType, typename T>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const AutoDiffScalar<DerType>& x, const T& y) {
-  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
-  return (x >= y ? ADS(x) : ADS(y));
-}
-template<typename DerType, typename T>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const T& x, const AutoDiffScalar<DerType>& y) {
-  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
-  return (x < y ? ADS(x) : ADS(y));
-}
-template<typename DerType, typename T>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const T& x, const AutoDiffScalar<DerType>& y) {
-  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
-  return (x > y ? ADS(x) : ADS(y));
-}
-template<typename DerType>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) {
-  return (x.value() < y.value() ? x : y);
-}
-template<typename DerType>
-inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) {
-  return (x.value() >= y.value() ? x : y);
-}
-
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs,
-  using std::abs;
-  return Eigen::MakeAutoDiffScalar(abs(x.value()), x.derivatives() * (x.value()<0 ? -1 : 1) );)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2,
-  using numext::abs2;
-  return Eigen::MakeAutoDiffScalar(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt,
-  using std::sqrt;
-  Scalar sqrtx = sqrt(x.value());
-  return Eigen::MakeAutoDiffScalar(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos,
-  using std::cos;
-  using std::sin;
-  return Eigen::MakeAutoDiffScalar(cos(x.value()), x.derivatives() * (-sin(x.value())));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin,
-  using std::sin;
-  using std::cos;
-  return Eigen::MakeAutoDiffScalar(sin(x.value()),x.derivatives() * cos(x.value()));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp,
-  using std::exp;
-  Scalar expx = exp(x.value());
-  return Eigen::MakeAutoDiffScalar(expx,x.derivatives() * expx);)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log,
-  using std::log;
-  return Eigen::MakeAutoDiffScalar(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
-
-template<typename DerType>
-inline const Eigen::AutoDiffScalar<
-EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<DerType>::type,typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar,product) >
-pow(const Eigen::AutoDiffScalar<DerType> &x, const typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar &y)
-{
-  using namespace Eigen;
-  using std::pow;
-  return Eigen::MakeAutoDiffScalar(pow(x.value(),y), x.derivatives() * (y * pow(x.value(),y-1)));
-}
-
-
-template<typename DerTypeA,typename DerTypeB>
-inline const AutoDiffScalar<Matrix<typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar,Dynamic,1> >
-atan2(const AutoDiffScalar<DerTypeA>& a, const AutoDiffScalar<DerTypeB>& b)
-{
-  using std::atan2;
-  typedef typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar Scalar;
-  typedef AutoDiffScalar<Matrix<Scalar,Dynamic,1> > PlainADS;
-  PlainADS ret;
-  ret.value() = atan2(a.value(), b.value());
-  
-  Scalar squared_hypot = a.value() * a.value() + b.value() * b.value();
-  
-  // if (squared_hypot==0) the derivation is undefined and the following results in a NaN:
-  ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) / squared_hypot;
-
-  return ret;
-}
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tan,
-  using std::tan;
-  using std::cos;
-  return Eigen::MakeAutoDiffScalar(tan(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cos(x.value()))));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin,
-  using std::sqrt;
-  using std::asin;
-  return Eigen::MakeAutoDiffScalar(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-numext::abs2(x.value()))));)
-  
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(acos,
-  using std::sqrt;
-  using std::acos;
-  return Eigen::MakeAutoDiffScalar(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-numext::abs2(x.value()))));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tanh,
-  using std::cosh;
-  using std::tanh;
-  return Eigen::MakeAutoDiffScalar(tanh(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cosh(x.value()))));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sinh,
-  using std::sinh;
-  using std::cosh;
-  return Eigen::MakeAutoDiffScalar(sinh(x.value()),x.derivatives() * cosh(x.value()));)
-
-EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cosh,
-  using std::sinh;
-  using std::cosh;
-  return Eigen::MakeAutoDiffScalar(cosh(x.value()),x.derivatives() * sinh(x.value()));)
-
-#undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY
-
-template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> >
-  : NumTraits< typename NumTraits<typename internal::remove_all<DerType>::type::Scalar>::Real >
-{
-  typedef typename internal::remove_all<DerType>::type DerTypeCleaned;
-  typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerTypeCleaned::Scalar>::Real,DerTypeCleaned::RowsAtCompileTime,DerTypeCleaned::ColsAtCompileTime,
-                                0, DerTypeCleaned::MaxRowsAtCompileTime, DerTypeCleaned::MaxColsAtCompileTime> > Real;
-  typedef AutoDiffScalar<DerType> NonInteger;
-  typedef AutoDiffScalar<DerType> Nested;
-  typedef typename NumTraits<typename DerTypeCleaned::Scalar>::Literal Literal;
-  enum{
-    RequireInitialization = 1
-  };
-};
-
-}
-
-namespace std {
-template <typename T>
-class numeric_limits<Eigen::AutoDiffScalar<T> >
-  : public numeric_limits<typename T::Scalar> {};
-
-}  // namespace std
-
-#endif // EIGEN_AUTODIFF_SCALAR_H
diff --git a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h b/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h
deleted file mode 100644
index 8c2d048..0000000
--- a/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h
+++ /dev/null
@@ -1,220 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// 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_AUTODIFF_VECTOR_H
-#define EIGEN_AUTODIFF_VECTOR_H
-
-namespace Eigen {
-
-/* \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)
-  *
-  * This class represents a scalar value while tracking its respective derivatives.
-  *
-  * It supports the following list of global math function:
-  *  - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos,
-  *  - internal::abs, internal::sqrt, numext::pow, internal::exp, internal::log, internal::sin, internal::cos,
-  *  - internal::conj, internal::real, internal::imag, numext::abs2.
-  *
-  * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However,
-  * in that case, the expression template mechanism only occurs at the top Matrix level,
-  * while derivatives are computed right away.
-  *
-  */
-template<typename ValueType, typename JacobianType>
-class AutoDiffVector
-{
-  public:
-    //typedef typename internal::traits<ValueType>::Scalar Scalar;
-    typedef typename internal::traits<ValueType>::Scalar BaseScalar;
-    typedef AutoDiffScalar<Matrix<BaseScalar,JacobianType::RowsAtCompileTime,1> > ActiveScalar;
-    typedef ActiveScalar Scalar;
-    typedef AutoDiffScalar<typename JacobianType::ColXpr> CoeffType;
-    typedef typename JacobianType::Index Index;
-
-    inline AutoDiffVector() {}
-
-    inline AutoDiffVector(const ValueType& values)
-      : m_values(values)
-    {
-      m_jacobian.setZero();
-    }
-
-
-    CoeffType operator[] (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType operator[] (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
-
-    CoeffType operator() (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType operator() (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
-
-    CoeffType coeffRef(Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType coeffRef(Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
-
-    Index size() const { return m_values.size(); }
-
-    // FIXME here we could return an expression of the sum
-    Scalar sum() const { /*std::cerr << "sum \n\n";*/ /*std::cerr << m_jacobian.rowwise().sum() << "\n\n";*/ return Scalar(m_values.sum(), m_jacobian.rowwise().sum()); }
-
-
-    inline AutoDiffVector(const ValueType& values, const JacobianType& jac)
-      : m_values(values), m_jacobian(jac)
-    {}
-
-    template<typename OtherValueType, typename OtherJacobianType>
-    inline AutoDiffVector(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
-      : m_values(other.values()), m_jacobian(other.jacobian())
-    {}
-
-    inline AutoDiffVector(const AutoDiffVector& other)
-      : m_values(other.values()), m_jacobian(other.jacobian())
-    {}
-
-    template<typename OtherValueType, typename OtherJacobianType>
-    inline AutoDiffVector& operator=(const AutoDiffVector<OtherValueType, OtherJacobianType>& other)
-    {
-      m_values = other.values();
-      m_jacobian = other.jacobian();
-      return *this;
-    }
-
-    inline AutoDiffVector& operator=(const AutoDiffVector& other)
-    {
-      m_values = other.values();
-      m_jacobian = other.jacobian();
-      return *this;
-    }
-
-    inline const ValueType& values() const { return m_values; }
-    inline ValueType& values() { return m_values; }
-
-    inline const JacobianType& jacobian() const { return m_jacobian; }
-    inline JacobianType& jacobian() { return m_jacobian; }
-
-    template<typename OtherValueType,typename OtherJacobianType>
-    inline const AutoDiffVector<
-      typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
-      typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >
-    operator+(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
-    {
-      return AutoDiffVector<
-      typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,ValueType,OtherValueType>::Type,
-      typename MakeCwiseBinaryOp<internal::scalar_sum_op<BaseScalar>,JacobianType,OtherJacobianType>::Type >(
-        m_values + other.values(),
-        m_jacobian + other.jacobian());
-    }
-
-    template<typename OtherValueType, typename OtherJacobianType>
-    inline AutoDiffVector&
-    operator+=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
-    {
-      m_values += other.values();
-      m_jacobian += other.jacobian();
-      return *this;
-    }
-
-    template<typename OtherValueType,typename OtherJacobianType>
-    inline const AutoDiffVector<
-      typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
-      typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >
-    operator-(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
-    {
-      return AutoDiffVector<
-        typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,ValueType,OtherValueType>::Type,
-        typename MakeCwiseBinaryOp<internal::scalar_difference_op<Scalar>,JacobianType,OtherJacobianType>::Type >(
-          m_values - other.values(),
-          m_jacobian - other.jacobian());
-    }
-
-    template<typename OtherValueType, typename OtherJacobianType>
-    inline AutoDiffVector&
-    operator-=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
-    {
-      m_values -= other.values();
-      m_jacobian -= other.jacobian();
-      return *this;
-    }
-
-    inline const AutoDiffVector<
-      typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type,
-      typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type >
-    operator-() const
-    {
-      return AutoDiffVector<
-        typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, ValueType>::Type,
-        typename MakeCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, JacobianType>::Type >(
-          -m_values,
-          -m_jacobian);
-    }
-
-    inline const AutoDiffVector<
-      typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
-      typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type>
-    operator*(const BaseScalar& other) const
-    {
-      return AutoDiffVector<
-        typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
-        typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >(
-          m_values * other,
-          m_jacobian * other);
-    }
-
-    friend inline const AutoDiffVector<
-      typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
-      typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >
-    operator*(const Scalar& other, const AutoDiffVector& v)
-    {
-      return AutoDiffVector<
-        typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, ValueType>::Type,
-        typename MakeCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>::Type >(
-          v.values() * other,
-          v.jacobian() * other);
-    }
-
-//     template<typename OtherValueType,typename OtherJacobianType>
-//     inline const AutoDiffVector<
-//       CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType>
-//       CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
-//         CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>,
-//         CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > >
-//     operator*(const AutoDiffVector<OtherValueType,OtherJacobianType>& other) const
-//     {
-//       return AutoDiffVector<
-//         CwiseBinaryOp<internal::scalar_multiple_op<Scalar>, ValueType, OtherValueType>
-//         CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
-//           CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, JacobianType>,
-//           CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, OtherJacobianType> > >(
-//             m_values.cwise() * other.values(),
-//             (m_jacobian * other.values()) + (m_values * other.jacobian()));
-//     }
-
-    inline AutoDiffVector& operator*=(const Scalar& other)
-    {
-      m_values *= other;
-      m_jacobian *= other;
-      return *this;
-    }
-
-    template<typename OtherValueType,typename OtherJacobianType>
-    inline AutoDiffVector& operator*=(const AutoDiffVector<OtherValueType,OtherJacobianType>& other)
-    {
-      *this = *this * other;
-      return *this;
-    }
-
-  protected:
-    ValueType m_values;
-    JacobianType m_jacobian;
-
-};
-
-}
-
-#endif // EIGEN_AUTODIFF_VECTOR_H