1 | // This file is part of Eigen, a lightweight C++ template library
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2 | // for linear algebra.
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3 | //
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4 | // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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5 | //
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6 | // This Source Code Form is subject to the terms of the Mozilla
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7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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9 |
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10 | #ifndef EIGEN_AUTODIFF_JACOBIAN_H
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11 | #define EIGEN_AUTODIFF_JACOBIAN_H
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12 |
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13 | namespace Eigen
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14 | {
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15 |
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16 | template<typename Functor> class AutoDiffJacobian : public Functor
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17 | {
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18 | public:
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19 | AutoDiffJacobian() : Functor() {}
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20 | AutoDiffJacobian(const Functor& f) : Functor(f) {}
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21 |
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22 | // forward constructors
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23 | template<typename T0>
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24 | AutoDiffJacobian(const T0& a0) : Functor(a0) {}
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25 | template<typename T0, typename T1>
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26 | AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {}
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27 | template<typename T0, typename T1, typename T2>
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28 | AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {}
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29 |
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30 | enum {
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31 | InputsAtCompileTime = Functor::InputsAtCompileTime,
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32 | ValuesAtCompileTime = Functor::ValuesAtCompileTime
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33 | };
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34 |
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35 | typedef typename Functor::InputType InputType;
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36 | typedef typename Functor::ValueType ValueType;
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37 | typedef typename Functor::JacobianType JacobianType;
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38 | typedef typename JacobianType::Scalar Scalar;
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39 | typedef typename JacobianType::Index Index;
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40 |
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41 | typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType;
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42 | typedef AutoDiffScalar<DerivativeType> ActiveScalar;
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43 |
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44 |
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45 | typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput;
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46 | typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue;
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47 |
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48 | void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const
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49 | {
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50 | eigen_assert(v!=0);
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51 | if (!_jac)
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52 | {
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53 | Functor::operator()(x, v);
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54 | return;
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55 | }
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56 |
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57 | JacobianType& jac = *_jac;
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58 |
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59 | ActiveInput ax = x.template cast<ActiveScalar>();
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60 | ActiveValue av(jac.rows());
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61 |
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62 | if(InputsAtCompileTime==Dynamic)
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63 | for (Index j=0; j<jac.rows(); j++)
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64 | av[j].derivatives().resize(this->inputs());
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65 |
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66 | for (Index i=0; i<jac.cols(); i++)
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67 | ax[i].derivatives() = DerivativeType::Unit(this->inputs(),i);
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68 |
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69 | Functor::operator()(ax, &av);
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70 |
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71 | for (Index i=0; i<jac.rows(); i++)
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72 | {
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73 | (*v)[i] = av[i].value();
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74 | jac.row(i) = av[i].derivatives();
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75 | }
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76 | }
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77 | protected:
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78 |
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79 | };
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80 |
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81 | }
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82 |
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83 | #endif // EIGEN_AUTODIFF_JACOBIAN_H
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