SOn.h

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/* ----------------------------------------------------------------------------
 
 * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
 * Atlanta, Georgia 30332-0415
 * All Rights Reserved
 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
 
 * See LICENSE for the license information
 
 * -------------------------------------------------------------------------- */

 
#pragma once
 
#include <gtsam/base/MatrixLieGroup.h>
#include <gtsam/dllexport.h>
 
#include <Eigen/Core>
#include <Eigen/Geometry>
 
#if GTSAM_ENABLE_BOOST_SERIALIZATION
#include <boost/serialization/nvp.hpp>
#endif
 
#include <iostream> // TODO(frank): how to avoid?
#include <string>
#include <type_traits>
#include <vector>
#include <random>
#include <cassert>
 
namespace gtsam {
 
namespace internal {
constexpr int DimensionSO(int N) {
  return (N < 0) ? Eigen::Dynamic : N * (N - 1) / 2;
}
 
// Calculate N^2 at compile time, or return Dynamic if so
constexpr int NSquaredSO(int N) { return (N < 0) ? Eigen::Dynamic : N * N; }
}  // namespace internal

template <int N>
class SO : public MatrixLieGroup<SO<N>, internal::DimensionSO(N), N> {
 public:
  inline constexpr static auto dimension = internal::DimensionSO(N);
  using MatrixNN = Eigen::Matrix<double, N, N>;
  using VectorN2 = Eigen::Matrix<double, internal::NSquaredSO(N), 1>;
  using MatrixDD = Eigen::Matrix<double, dimension, dimension>;

  using LieAlgebra = MatrixNN;
 
 protected:
  MatrixNN matrix_;  
 
  // enable_if_t aliases, used to specialize constructors/methods, see
  // https://www.fluentcpp.com/2018/05/18/make-sfinae-pretty-2-hidden-beauty-sfinae/
  template <int N_>
  using IsDynamic = typename std::enable_if<N_ == Eigen::Dynamic, void>::type;
  template <int N_>
  using IsFixed = typename std::enable_if<N_ >= 2, void>::type;
  template <int N_>
  using IsSO3 = typename std::enable_if<N_ == 3, void>::type;
 
 public:

  template <int N_ = N, typename = IsFixed<N_>>
  SO() : matrix_(MatrixNN::Identity()) {}

  template <int N_ = N, typename = IsDynamic<N_>>
  explicit SO(size_t n = 0) {
    // We allow for n=0 as the default constructor, needed for serialization,
    // wrappers etc.
    matrix_ = Eigen::MatrixXd::Identity(n, n);
  }

  template <typename Derived>
  explicit SO(const Eigen::MatrixBase<Derived>& R) : matrix_(R.eval()) {}

  template <typename Derived>
  static SO FromMatrix(const Eigen::MatrixBase<Derived>& R) {
    return SO(R);
  }

  template <typename Derived, int N_ = N, typename = IsDynamic<N_>>
  static SO Lift(size_t n, const Eigen::MatrixBase<Derived> &R) {
    Matrix Q = Matrix::Identity(n, n);
    const int p = R.rows();
    assert(p >= 0 && p <= static_cast<int>(n) && R.cols() == p);
    Q.topLeftCorner(p, p) = R;
    return SO(Q);
  }

  template <int M, int N_ = N, typename = IsDynamic<N_>>
  explicit SO(const SO<M>& R) : matrix_(R.matrix()) {}

  template <int N_ = N, typename = IsSO3<N_>>
  explicit SO(const Eigen::AngleAxisd& angleAxis) : matrix_(angleAxis) {}

  static SO AxisAngle(const Vector3& axis, double theta);

  static SO ClosestTo(const MatrixNN& M);

  static SO ChordalMean(const std::vector<SO>& rotations);

  template <int N_ = N, typename = IsDynamic<N_>>
  static SO Random(std::mt19937& rng, size_t n = 0) {
    if (n == 0) throw std::runtime_error("SO: Dimensionality not known.");
    // TODO(frank): this might need to be re-thought
    static std::uniform_real_distribution<double> randomAngle(-M_PI, M_PI);
    const size_t d = SO::Dimension(n);
    Vector xi(d);
    for (size_t j = 0; j < d; j++) {
      xi(j) = randomAngle(rng);
    }
    return SO::Retract(xi);
  }

  template <int N_ = N, typename = IsFixed<N_>>
  static SO Random(std::mt19937& rng) {
    // By default, use dynamic implementation above. Specialized for SO(3).
    return SO(SO<Eigen::Dynamic>::Random(rng, N).matrix());
  }


  const MatrixNN& matrix() const { return matrix_; }
 
  size_t rows() const { return matrix_.rows(); }
  size_t cols() const { return matrix_.cols(); }

 
  void print(const std::string& s = std::string()) const;
 
  bool equals(const SO& other, double tol) const {
    return equal_with_abs_tol(matrix_, other.matrix_, tol);
  }


  SO operator*(const SO& other) const {
    assert(dim() == other.dim());
    return SO(matrix_ * other.matrix_);
  }

  template <int N_ = N, typename = IsFixed<N_>>
  static SO Identity() {
    return SO();
  }

  template <int N_ = N, typename = IsDynamic<N_>>
  static SO Identity(size_t n = 0) {
    return SO(n);
  }

  SO inverse() const { return SO(matrix_.transpose()); }

 
  using TangentVector = Eigen::Matrix<double, dimension, 1>;
  using ChartJacobian = OptionalJacobian<dimension, dimension>;
 
  // Calculate manifold dimensionality for SO(n).
  // Available as dimension or Dim() for fixed N.
  static size_t Dimension(size_t n) { return n * (n - 1) / 2; }
 
  // Calculate ambient dimension n from manifold dimensionality d.
  static size_t AmbientDim(size_t d) { return (1 + std::sqrt(1 + 8 * d)) / 2; }
 
  // Calculate run-time dimensionality of manifold.
  size_t dim() const { return Dimension(static_cast<size_t>(matrix_.rows())); }

  static MatrixNN Hat(const TangentVector& xi);

  static void Hat(const Vector &xi, Eigen::Ref<MatrixNN> X);

  static TangentVector Vee(const MatrixNN& X);
 
  // Chart at origin
  struct ChartAtOrigin {
    static SO Retract(const TangentVector& xi);

    static SO Retract(const TangentVector& xi, ChartJacobian H) = delete;

    static TangentVector Local(const SO& R);

    static TangentVector Local(const SO& R, ChartJacobian H) = delete;
  };
 
  // Return dynamic identity DxD Jacobian for given SO(n)
  template <int N_ = N, typename = IsDynamic<N_>>
  static MatrixDD IdentityJacobian(size_t n) {
    const size_t d = Dimension(n);
    return MatrixDD::Identity(d, d);
  }


  MatrixDD AdjointMap() const {
    return MatrixLieGroup<SO<N>, internal::DimensionSO(N), N>::AdjointMap();
  }

  static SO Expmap(const TangentVector& omega);

  static SO Expmap(const TangentVector& omega, ChartJacobian H) = delete;

  static MatrixDD ExpmapDerivative(const TangentVector& omega) = delete;

  static TangentVector Logmap(const SO& R);

  static TangentVector Logmap(const SO& R, ChartJacobian H) = delete;

  static MatrixDD LogmapDerivative(const TangentVector& omega) = delete;
 
  // inverse with optional derivative
  using LieGroup<SO<N>, internal::DimensionSO(N)>::inverse;


  VectorN2 vec(OptionalJacobian<internal::NSquaredSO(N), dimension> H =
    {}) const {
    return MatrixLieGroup<SO<N>, internal::DimensionSO(N), N>::vec(H);
  }

  template <int N_ = N, typename = IsFixed<N_>>
  static Matrix VectorizedGenerators() {
    constexpr size_t N2 = static_cast<size_t>(N * N);
    Eigen::Matrix<double, N2, dimension> G;
    for (size_t j = 0; j < dimension; j++) {
      const auto X = Hat(Vector::Unit(dimension, j));
      G.col(j) = Eigen::Map<const VectorN2>(X.data());
    }
    return G;
  }

  template <int N_ = N, typename = IsDynamic<N_>>
  static Matrix VectorizedGenerators(size_t n = 0) {
    const size_t n2 = n * n, dim = Dimension(n);
    Matrix G(n2, dim);
    for (size_t j = 0; j < dim; j++) {
      const auto X = Hat(Vector::Unit(dim, j));
      G.col(j) = Eigen::Map<const Matrix>(X.data(), n2, 1);
    }
    return G;
  }

 
#if GTSAM_ENABLE_BOOST_SERIALIZATION
  template <class Archive>
  friend void save(Archive&, SO&, const unsigned int);
  template <class Archive>
  friend void load(Archive&, SO&, const unsigned int);
  template <class Archive>
  friend void serialize(Archive&, SO&, const unsigned int);
  friend class boost::serialization::access;
  friend class Rot3;  // for serialize
#endif

};
 
using SOn = SO<Eigen::Dynamic>;
 
/*
 * Specialize dynamic Hat and Vee, because recursion depends on dynamic nature.
 * The definition is in SOn.cpp. Fixed-size SO3 and SO4 have their own version,
 * and implementation for other fixed N is in SOn-inl.h.
 */
 
template <>
GTSAM_EXPORT
Matrix SOn::Hat(const Vector& xi);
 
template <>
GTSAM_EXPORT
Vector SOn::Vee(const Matrix& X);
 
/*
 * Specialize dynamic compose and between, because the derivative is unknowable
 * by the LieGroup implementations, who return a fixed-size matrix for H2.
 */
 
using DynamicJacobian = OptionalJacobian<Eigen::Dynamic, Eigen::Dynamic>;
 
template <>
GTSAM_EXPORT
SOn LieGroup<SOn, Eigen::Dynamic>::compose(const SOn& g, DynamicJacobian H1,
                                           DynamicJacobian H2) const;
 
template <>
GTSAM_EXPORT
SOn LieGroup<SOn, Eigen::Dynamic>::between(const SOn& g, DynamicJacobian H1,
                                           DynamicJacobian H2) const;
 
#if GTSAM_ENABLE_BOOST_SERIALIZATION
template<class Archive>
void serialize(
  Archive& ar, SOn& Q,
  const unsigned int file_version
) {
  Matrix& M = Q.matrix_;
  ar& BOOST_SERIALIZATION_NVP(M);
}
#endif
 
/*
 * Define the traits. internal::MatrixLieGroup provides both Lie group and Testable
 */
 
template <int N>
struct traits<SO<N>> : public internal::MatrixLieGroup<SO<N>, N> {};
 
template <int N>
struct traits<const SO<N>> : public internal::MatrixLieGroup<SO<N>, N> {};
 
}  // namespace gtsam
 
#include "SOn-inl.h"