utils.hpp

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#pragma once
 
#include "lqr-problem.hpp"
#include <boost/core/span.hpp>
#include <Eigen/SparseCore>
 
namespace aligator::gar {
namespace helpers {
template <typename InType, typename OutScalar>
void sparseAssignDenseBlock(Eigen::Index i0, Eigen::Index j0,
                            const Eigen::DenseBase<InType> &input,
                            Eigen::SparseMatrix<OutScalar> &out, bool update) {
  assert(i0 + input.rows() <= out.rows() && "Inconsistent rows");
  assert(j0 + input.cols() <= out.cols() && "Inconsistent cols");
  using Eigen::Index;
  for (Index i = 0; i < input.rows(); i++) {
    for (Index j = 0; j < input.cols(); j++) {
      if (update)
        out.coeffRef(i0 + i, j0 + j) = input(i, j);
      else
        out.insert(i0 + i, j0 + j) = input(i, j);
    }
  }
}
 
template <typename Scalar>
void sparseAssignDiagonal(Eigen::Index i0, Eigen::Index i1, Scalar value,
                          Eigen::SparseMatrix<Scalar> &out, bool update) {
  using Eigen::Index;
  assert(i0 <= i1 && "i0 should be lesser than i1. Can't assign empty range.");
  assert(i1 <= out.rows() && "Inconsistent rows");
  assert(i1 <= out.cols() && "Inconsistent cols");
  for (Index kk = i0; kk < i1; kk++) {
    if (update)
      out.coeffRef(kk, kk) = value;
    else
      out.insert(kk, kk) = value;
  }
}
} // namespace helpers
 
template <typename Scalar>
void lqrCreateSparseMatrix(const LqrProblemTpl<Scalar> &problem,
                           const Scalar mueq, Eigen::SparseMatrix<Scalar> &mat,
                           Eigen::Matrix<Scalar, -1, 1> &rhs, bool update);
 
template <typename Scalar>
[[nodiscard]] std::array<Scalar, 3> lqrComputeKktError(
    const LqrProblemTpl<Scalar> &problem,
    boost::span<const typename math_types<Scalar>::VectorXs> xs,
    boost::span<const typename math_types<Scalar>::VectorXs> us,
    boost::span<const typename math_types<Scalar>::VectorXs> vs,
    boost::span<const typename math_types<Scalar>::VectorXs> lbdas,
    const Scalar mueq,
    const std::optional<typename math_types<Scalar>::ConstVectorRef> &theta =
        std::nullopt,
    bool verbose = false);

template <typename Scalar>
uint lqrNumRows(const LqrProblemTpl<Scalar> &problem) {
  const auto &knots = problem.stages;
  const uint nc0 = problem.nc0();
  const size_t N = knots.size() - 1UL;
  uint nrows = nc0;
  for (size_t t = 0; t <= N; t++) {
    const auto &model = knots[t];
    nrows += model.nx + model.nu + model.nc;
    if (t != N)
      nrows += model.nx;
  }
  return nrows;
}

template <typename Scalar>
void lqrDenseSolutionToTraj(
    const LqrProblemTpl<Scalar> &problem,
    const typename math_types<Scalar>::ConstVectorRef solution,
    std::vector<typename math_types<Scalar>::VectorXs> &xs,
    std::vector<typename math_types<Scalar>::VectorXs> &us,
    std::vector<typename math_types<Scalar>::VectorXs> &vs,
    std::vector<typename math_types<Scalar>::VectorXs> &lbdas) {
  const uint N = (uint)problem.horizon();
  xs.resize(N + 1);
  us.resize(N + 1);
  vs.resize(N + 1);
  lbdas.resize(N + 1);
  const uint nc0 = problem.nc0();
 
  lbdas[0] = solution.head(nc0);
 
  uint idx = nc0;
  for (size_t t = 0; t <= N; t++) {
    const LqrKnotTpl<Scalar> &knot = problem.stages[t];
    const uint n = knot.nx + knot.nu + knot.nc;
    auto seg = solution.segment(idx, n);
    xs[t] = seg.head(knot.nx);
    us[t] = seg.segment(knot.nx, knot.nu);
    vs[t] = seg.segment(knot.nx + knot.nu, knot.nc);
    idx += n;
    if (t < N) {
      lbdas[t + 1] = solution.segment(idx, knot.nx2);
      idx += knot.nx2;
    }
  }
}
 
template <typename Scalar>
[[nodiscard]] auto lqrInitializeSolution(const LqrProblemTpl<Scalar> &problem) {
  using VectorXs = typename math_types<Scalar>::VectorXs;
  std::vector<VectorXs> xs;
  std::vector<VectorXs> us;
  std::vector<VectorXs> vs;
  std::vector<VectorXs> lbdas;
  const uint N = (uint)problem.horizon();
 
  xs.resize(N + 1);
  us.resize(N + 1);
  vs.resize(N + 1);
  lbdas.resize(N + 1);
 
  lbdas[0].setZero(problem.nc0());
  for (uint i = 0; i <= N; i++) {
    const LqrKnotTpl<Scalar> &kn = problem.stages[i];
    xs[i].setZero(kn.nx);
    us[i].setZero(kn.nu);
    vs[i].setZero(kn.nc);
    if (i == N)
      break;
    lbdas[i + 1].setZero(kn.nx2);
  }
  if (problem.stages.back().nu == 0) {
    us.pop_back();
  }
  return std::make_tuple(std::move(xs), std::move(us), std::move(vs),
                         std::move(lbdas));
}
 
#ifdef ALIGATOR_ENABLE_TEMPLATE_INSTANTIATION
extern template void lqrCreateSparseMatrix<context::Scalar>(
    const LqrProblemTpl<context::Scalar> &problem, const context::Scalar mueq,
    Eigen::SparseMatrix<context::Scalar> &mat, context::VectorXs &rhs,
    bool update);
extern template std::array<context::Scalar, 3>
lqrComputeKktError<context::Scalar>(
    const LqrProblemTpl<context::Scalar> &,
    boost::span<const context::VectorXs>, boost::span<const context::VectorXs>,
    boost::span<const context::VectorXs>, boost::span<const context::VectorXs>,
    const context::Scalar, const std::optional<context::ConstVectorRef> &,
    bool);
#endif
 
} // namespace aligator::gar