From f0238cfb6997c4acfc2bd200de7295f3fa36968f Mon Sep 17 00:00:00 2001
From: Stanislaw Halik <sthalik@misaki.pl>
Date: Sun, 3 Mar 2019 21:09:10 +0100
Subject: don't index Eigen

---
 .../Eigen/src/AutoDiff/AutoDiffJacobian.h          | 108 ---------------------
 1 file changed, 108 deletions(-)
 delete mode 100644 eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h

(limited to 'eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h')

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
-- 
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