//
// Copyright (c) 2015-2018 CNRS
//

/*
 * Compare the value obtained with the RNEA with the values obtained from
 * RBDL. The test is not complete. It only validates the RNEA for the revolute
 * joints. The free-flyer is not tested. It should be extended to account for
 * the free flyer and for the other algorithms.
 *
 * Additionnal notes: the RNEA is an algorithm that can be used to validate
 * many others (in particular, the mass matrix (CRBA) can be numerically
 * validated from the RNEA, then the center-of-mass jacobian can be validated
 * from the mass matrix, etc.
 *
 */

#include <iostream>
#include <iomanip>

#include "pinocchio/multibody.hpp"
#include "pinocchio/parsers/urdf.hpp"
#include "pinocchio/algorithm/rnea.hpp"

#include <boost/test/unit_test.hpp>

BOOST_AUTO_TEST_SUITE(BOOST_TEST_MODULE)

BOOST_AUTO_TEST_CASE(test_000)
{
  std::string filename = PINOCCHIO_MODEL_DIR + std::string("/simple_humanoid.urdf");

  pinocchio::Model model;
  pinocchio::urdf::buildModel(filename, pinocchio::JointModelFreeFlyer(), model);
  model.gravity.linear(Eigen::Vector3d(0, 0, -9.8));
  pinocchio::Data data(model);

  Eigen::VectorXd q = Eigen::VectorXd::Zero(model.nq);
  Eigen::VectorXd v = Eigen::VectorXd::Zero(model.nv);
  Eigen::VectorXd a = Eigen::VectorXd::Zero(model.nv);

  std::cout << std::setprecision(10);

  Eigen::VectorXd expected(model.nv);
  expected << 0, 0, 1281.84, 0, -40.5132, 0, 4.4492, -1.5386, 0, -1.5386, -1.5386, 0, -4.4492,
    -1.5386, 0, -1.5386, -1.5386, 0, -37.436, 0, 0, -2.548, 0, 0, 0.392, 0, 0.392, 0, -2.548, 0, 0,
    0.392, 0, 0.392, 0;
  q = Eigen::VectorXd::Zero(model.nq);
  v = Eigen::VectorXd::Zero(model.nv);
  a = Eigen::VectorXd::Zero(model.nv);
  rnea(model, data, q, v, a);
  BOOST_CHECK(expected.isApprox(data.tau, 1e-12));
}

BOOST_AUTO_TEST_CASE(test_0V0)
{
  std::string filename = PINOCCHIO_MODEL_DIR + std::string("/simple_humanoid.urdf");

  pinocchio::Model model;
  pinocchio::urdf::buildModel(filename, pinocchio::JointModelFreeFlyer(), model);
  model.gravity.linear(Eigen::Vector3d(0, 0, -9.8));
  pinocchio::Data data(model);

  Eigen::VectorXd q = Eigen::VectorXd::Zero(model.nq);
  Eigen::VectorXd v = Eigen::VectorXd::Zero(model.nv);
  Eigen::VectorXd a = Eigen::VectorXd::Zero(model.nv);

  std::cout << std::setprecision(10);

  Eigen::VectorXd expected(model.nv);
  expected << -48.10636, -73.218816, 1384.901025, -7.2292939, -186.342371, -20.6685852, -0.78887946,
    -1.869651075, 1.8889752, -2.036768175, -2.105948175, -1.023232, -18.3738505, -4.133954895,
    9.0456456, -4.276615035, -4.143427035, -2.534896, -180.338765, 15.71570676, -29.8639164,
    -59.917862, -2.3307916, -2.7648728, -45.76782776, 3.4151272, -18.4320456, -4.5768072,
    -76.60945104, -0.5897908, -2.640844, -63.93417064, 5.359156, -25.8309196, -6.976116;
  q = Eigen::VectorXd::Zero(model.nq);
  for (int i = 6; i < model.nv; ++i)
    v[i] = i / 10.;
  a = Eigen::VectorXd::Zero(model.nv);
  rnea(model, data, q, v, a);
  // std::cout << (expected-data.tau).norm() << std::endl;
  BOOST_CHECK(expected.isApprox(data.tau, 1e-7));
}

BOOST_AUTO_TEST_CASE(test_0VA)
{
  std::string filename = PINOCCHIO_MODEL_DIR + std::string("/simple_humanoid.urdf");

  pinocchio::Model model;
  pinocchio::urdf::buildModel(filename, pinocchio::JointModelFreeFlyer(), model);
  model.gravity.linear(Eigen::Vector3d(0, 0, -9.8));
  pinocchio::Data data(model);

  Eigen::VectorXd q = Eigen::VectorXd::Zero(model.nq);
  Eigen::VectorXd v = Eigen::VectorXd::Zero(model.nv);
  Eigen::VectorXd a = Eigen::VectorXd::Zero(model.nv);

  std::cout << std::setprecision(10);
  Eigen::VectorXd expected(model.nv);
  expected << -15.3331636, -0.67891816, 1273.80521, 102.9435113, 110.3509945, 81.52296995,
    13.31476408, 14.26606068, 3.682505252, 9.048274318, 4.663303518, 2.05308568, 12.54347834,
    25.92680911, 6.327105656, 16.71123385, 8.96650473, 3.54200704, 70.15812475, 77.02410963,
    73.81994844, 41.73185754, 28.75786872, 28.94251127, 31.65847724, 20.40431127, 18.18579154,
    6.838471928, 50.44193173, 34.07362801, 34.53507156, 38.33983417, 24.61507156, 22.2842788,
    8.23435884;
  q = Eigen::VectorXd::Zero(model.nq);
  for (int i = 6; i < model.nv; ++i)
    v[i] = i / 100.;
  for (int i = 6; i < model.nv; ++i)
    a[i] = i / 10.;
  rnea(model, data, q, v, a);
  BOOST_CHECK(expected.isApprox(data.tau, 1e-6));
}

BOOST_AUTO_TEST_CASE(test_Q00)
{
  std::string filename = PINOCCHIO_MODEL_DIR + std::string("/simple_humanoid.urdf");

  pinocchio::Model model;
  pinocchio::urdf::buildModel(filename, pinocchio::JointModelFreeFlyer(), model);
  model.gravity.linear(Eigen::Vector3d(0, 0, -9.8));
  pinocchio::Data data(model);

  Eigen::VectorXd q = Eigen::VectorXd::Zero(model.nq);
  Eigen::VectorXd v = Eigen::VectorXd::Zero(model.nv);
  Eigen::VectorXd a = Eigen::VectorXd::Zero(model.nv);

  std::cout << std::setprecision(10);

  Eigen::VectorXd expected(model.nv);
  expected << 5.367234435e-15, -2.587860481e-14, 1281.84, -133.3062501, 198.975587,
    -7.120345979e-16, 15.06850407, 58.39287139, -22.14971864, 17.14327289, 1.291543104,
    0.7402017048, -4.386231387, 22.73949408, -19.01681794, 0.8839600793, -0.3197599308,
    -0.466827706, 65.47086697, 32.71449398, -4.250622066, -0.7937685568, -0.15349648, -1.070480752,
    -3.066302263, -0.3557903212, -0.2183951073, 0.182684221, -0.6648425468, -2.902772493,
    0.1250340934, 0.4402877138, -0.3158584741, -0.0865162794, 0.3918733239;
  for (int i = 7; i < model.nq; ++i)
    q[i] = (i - 1) / 10.;
  v = Eigen::VectorXd::Zero(model.nv);
  a = Eigen::VectorXd::Zero(model.nv);
  rnea(model, data, q, v, a);
  //  std::cout << expected << "\n ---------------- \n"
  //            << data.tau << std::endl;

  BOOST_CHECK(expected.isApprox(data.tau, 1e-6));
}

BOOST_AUTO_TEST_CASE(test_QVA)
{
  std::string filename = PINOCCHIO_MODEL_DIR + std::string("/simple_humanoid.urdf");

  pinocchio::Model model;
  pinocchio::urdf::buildModel(filename, pinocchio::JointModelFreeFlyer(), model);
  model.gravity.linear(Eigen::Vector3d(0, 0, -9.8));
  pinocchio::Data data(model);

  Eigen::VectorXd q = Eigen::VectorXd::Zero(model.nq);
  Eigen::VectorXd v = Eigen::VectorXd::Zero(model.nv);
  Eigen::VectorXd a = Eigen::VectorXd::Zero(model.nv);

  std::cout << std::setprecision(10);
  Eigen::VectorXd expected(model.nv);
  expected << -1.911650826, 1.250211406, 1284.82058, -139.0188156, 201.744449, 1.554847332,
    15.1910084, 59.27339983, -21.70753738, 17.84339797, 1.754639468, 0.670280632, -2.968778954,
    23.0776205, -17.56870284, 1.765761886, 0.2889992363, -0.392159764, 68.83598707, 34.59002827,
    -4.604435817, -0.3832225891, 1.085231916, -0.348635267, -2.831371037, -1.047616506,
    -0.228384161, 0.5656880079, 1.302869049, 0.8481280783, 0.7042182131, 1.554751317, -0.3908790552,
    -0.1294643218, 1.421077555;
  for (int i = 7; i < model.nq; ++i)
    q[i] = (i - 1) / 10.;
  for (int i = 6; i < model.nv; ++i)
    v[i] = i / 100.;
  for (int i = 6; i < model.nv; ++i)
    a[i] = i / 100.;
  rnea(model, data, q, v, a);
  BOOST_CHECK(expected.isApprox(data.tau, 1e-7));
}

BOOST_AUTO_TEST_SUITE_END()
