// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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/.
// SPDX-License-Identifier: MPL-2.0

#include "main.h"
#include <Eigen/Dense>

#define NUMBER_DIRECTIONS 16
#include <contrib/Eigen/AdolcForward>

template <typename Vector>
EIGEN_DONT_INLINE typename Vector::Scalar foo(const Vector& p) {
  typedef typename Vector::Scalar Scalar;
  return (p - Vector(Scalar(-1), Scalar(1.))).norm() + (p.array().sqrt().abs() * p.array().sin()).sum() + p.dot(p);
}

template <typename Scalar_, int NX = Dynamic, int NY = Dynamic>
struct TestFunc1 {
  typedef Scalar_ Scalar;
  enum { InputsAtCompileTime = NX, ValuesAtCompileTime = NY };
  typedef Matrix<Scalar, InputsAtCompileTime, 1> InputType;
  typedef Matrix<Scalar, ValuesAtCompileTime, 1> ValueType;
  typedef Matrix<Scalar, ValuesAtCompileTime, InputsAtCompileTime> JacobianType;

  int m_inputs, m_values;

  TestFunc1() : m_inputs(InputsAtCompileTime), m_values(ValuesAtCompileTime) {}
  TestFunc1(int inputs_, int values_) : m_inputs(inputs_), m_values(values_) {}

  int inputs() const { return m_inputs; }
  int values() const { return m_values; }

  template <typename T>
  void operator()(const Matrix<T, InputsAtCompileTime, 1>& x, Matrix<T, ValuesAtCompileTime, 1>* _v) const {
    Matrix<T, ValuesAtCompileTime, 1>& v = *_v;

    v[0] = 2 * x[0] * x[0] + x[0] * x[1];
    v[1] = 3 * x[1] * x[0] + 0.5 * x[1] * x[1];
    if (inputs() > 2) {
      v[0] += 0.5 * x[2];
      v[1] += x[2];
    }
    if (values() > 2) {
      v[2] = 3 * x[1] * x[0] * x[0];
    }
    if (inputs() > 2 && values() > 2) v[2] *= x[2];
  }

  void operator()(const InputType& x, ValueType* v, JacobianType* _j) const {
    (*this)(x, v);

    if (_j) {
      JacobianType& j = *_j;

      j(0, 0) = 4 * x[0] + x[1];
      j(1, 0) = 3 * x[1];

      j(0, 1) = x[0];
      j(1, 1) = 3 * x[0] + 2 * 0.5 * x[1];

      if (inputs() > 2) {
        j(0, 2) = 0.5;
        j(1, 2) = 1;
      }
      if (values() > 2) {
        j(2, 0) = 3 * x[1] * 2 * x[0];
        j(2, 1) = 3 * x[0] * x[0];
      }
      if (inputs() > 2 && values() > 2) {
        j(2, 0) *= x[2];
        j(2, 1) *= x[2];

        j(2, 2) = 3 * x[1] * x[0] * x[0];
        j(2, 2) = 3 * x[1] * x[0] * x[0];
      }
    }
  }
};

template <typename Func>
void adolc_forward_jacobian(const Func& f) {
  typename Func::InputType x = Func::InputType::Random(f.inputs());
  typename Func::ValueType y(f.values()), yref(f.values());
  typename Func::JacobianType j(f.values(), f.inputs()), jref(f.values(), f.inputs());

  jref.setZero();
  yref.setZero();
  f(x, &yref, &jref);
  //     std::cerr << y.transpose() << "\n\n";;
  //     std::cerr << j << "\n\n";;

  j.setZero();
  y.setZero();
  AdolcForwardJacobian<Func> autoj(f);
  autoj(x, &y, &j);
  //     std::cerr << y.transpose() << "\n\n";;
  //     std::cerr << j << "\n\n";;

  VERIFY_IS_APPROX(y, yref);
  VERIFY_IS_APPROX(j, jref);
}

EIGEN_DECLARE_TEST(forward_adolc) {
  adtl::setNumDir(NUMBER_DIRECTIONS);

  for (int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST((adolc_forward_jacobian(TestFunc1<double, 2, 2>())));
    CALL_SUBTEST((adolc_forward_jacobian(TestFunc1<double, 2, 3>())));
    CALL_SUBTEST((adolc_forward_jacobian(TestFunc1<double, 3, 2>())));
    CALL_SUBTEST((adolc_forward_jacobian(TestFunc1<double, 3, 3>())));
    CALL_SUBTEST((adolc_forward_jacobian(TestFunc1<double>(3, 3))));
  }

  {
    // simple instantiation tests
    Matrix<adtl::adouble, 2, 1> x;
    foo(x);
    Matrix<adtl::adouble, Dynamic, Dynamic> A(4, 4);
    ;
    A.selfadjointView<Lower>().eigenvalues();
  }
}