eiquadprog-rt.hpp

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//
// Copyright (c) 2017 CNRS
//
// This file is part of eiquadprog.
//
// eiquadprog is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
//(at your option) any later version.
 
// eiquadprog is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Lesser General Public License for more details.
 
// You should have received a copy of the GNU Lesser General Public License
// along with eiquadprog.  If not, see <https://www.gnu.org/licenses/>.
 
#ifndef __eiquadprog_rt_hpp__
#define __eiquadprog_rt_hpp__
 
#include <Eigen/Dense>
 
#include "eiquadprog/eiquadprog-utils.hxx"
 
#define OPTIMIZE_STEP_1_2         // compute s(x) = ci^T * x + ci0
#define OPTIMIZE_COMPUTE_D        // use noalias
#define OPTIMIZE_UPDATE_Z         // use noalias
#define OPTIMIZE_HESSIAN_INVERSE  // use solveInPlace
#define OPTIMIZE_UNCONSTR_MINIM
 
// #define USE_WARM_START
// #define PROFILE_EIQUADPROG
// #define DEBUG_STREAM(msg) std::cout<<msg;
#define DEBUG_STREAM(msg)
 
#ifdef PROFILE_EIQUADPROG
#define START_PROFILER_EIQUADPROG_RT(x) START_PROFILER(x)
#define STOP_PROFILER_EIQUADPROG_RT(x) STOP_PROFILER(x)
#else
#define START_PROFILER_EIQUADPROG_RT(x)
#define STOP_PROFILER_EIQUADPROG_RT(x)
#endif
 
#define PROFILE_EIQUADPROG_CHOWLESKY_DECOMPOSITION "EIQUADPROG_RT Chowlesky dec"
#define PROFILE_EIQUADPROG_CHOWLESKY_INVERSE "EIQUADPROG_RT Chowlesky inv"
#define PROFILE_EIQUADPROG_ADD_EQ_CONSTR "EIQUADPROG_RT ADD_EQ_CONSTR"
#define PROFILE_EIQUADPROG_ADD_EQ_CONSTR_1 "EIQUADPROG_RT ADD_EQ_CONSTR_1"
#define PROFILE_EIQUADPROG_ADD_EQ_CONSTR_2 "EIQUADPROG_RT ADD_EQ_CONSTR_2"
#define PROFILE_EIQUADPROG_STEP_1 "EIQUADPROG_RT STEP_1"
#define PROFILE_EIQUADPROG_STEP_1_1 "EIQUADPROG_RT STEP_1_1"
#define PROFILE_EIQUADPROG_STEP_1_2 "EIQUADPROG_RT STEP_1_2"
#define PROFILE_EIQUADPROG_STEP_1_UNCONSTR_MINIM \
  "EIQUADPROG_RT STEP_1_UNCONSTR_MINIM"
#define PROFILE_EIQUADPROG_STEP_2 "EIQUADPROG_RT STEP_2"
#define PROFILE_EIQUADPROG_STEP_2A "EIQUADPROG_RT STEP_2A"
#define PROFILE_EIQUADPROG_STEP_2B "EIQUADPROG_RT STEP_2B"
#define PROFILE_EIQUADPROG_STEP_2C "EIQUADPROG_RT STEP_2C"
 
#define DEFAULT_MAX_ITER 1000
 
template <int Rows, int Cols>
struct RtMatrixX {
  typedef Eigen::Matrix<double, Rows, Cols> d;
};
 
template <int Rows>
struct RtVectorX {
  typedef Eigen::Matrix<double, Rows, 1> d;
  typedef Eigen::Matrix<int, Rows, 1> i;
};
 
namespace eiquadprog {
 
namespace solvers {
 
enum RtEiquadprog_status {
  RT_EIQUADPROG_OPTIMAL = 0,
  RT_EIQUADPROG_INFEASIBLE = 1,
  RT_EIQUADPROG_UNBOUNDED = 2,
  RT_EIQUADPROG_MAX_ITER_REACHED = 3,
  RT_EIQUADPROG_REDUNDANT_EQUALITIES = 4
};
 
template <int nVars, int nEqCon, int nIneqCon>
class RtEiquadprog {
 public:
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
 
  RtEiquadprog();
  virtual ~RtEiquadprog();
 
  int getMaxIter() const { return m_maxIter; }
 
  bool setMaxIter(int maxIter) {
    if (maxIter < 0) return false;
    m_maxIter = maxIter;
    return true;
  }
 
  int getActiveSetSize() const { return q; }
 
  int getIteratios() const { return iter; }
 
  double getObjValue() const { return f_value; }
 
  const typename RtVectorX<nIneqCon + nEqCon>::d& getLagrangeMultipliers()
      const {
    return u;
  }
 
  const typename RtVectorX<nIneqCon + nEqCon>::i& getActiveSet() const {
    return A;
  }
 
  RtEiquadprog_status solve_quadprog(
      const typename RtMatrixX<nVars, nVars>::d& Hess,
      const typename RtVectorX<nVars>::d& g0,
      const typename RtMatrixX<nEqCon, nVars>::d& CE,
      const typename RtVectorX<nEqCon>::d& ce0,
      const typename RtMatrixX<nIneqCon, nVars>::d& CI,
      const typename RtVectorX<nIneqCon>::d& ci0,
      typename RtVectorX<nVars>::d& x);
 
  typename RtMatrixX<nVars, nVars>::d m_J;  // J * J' = Hessian
  bool is_inverse_provided_;
 
 private:
  int m_maxIter;   
  double f_value;  
 
  Eigen::LLT<typename RtMatrixX<nVars, nVars>::d, Eigen::Lower> chol_;
  double solver_return_;
 
  typename RtMatrixX<nVars, nVars>::d R;
 
  typename RtVectorX<nIneqCon>::d s;
 
  typename RtVectorX<nIneqCon + nEqCon>::d r;
 
  typename RtVectorX<nIneqCon + nEqCon>::d u;
 
  typename RtVectorX<nVars>::d z;
 
  typename RtVectorX<nVars>::d d;
 
  typename RtVectorX<nVars>::d np;
 
  typename RtVectorX<nIneqCon + nEqCon>::i A;
 
  typename RtVectorX<nIneqCon>::i iai;
 
  typename RtVectorX<nIneqCon>::i iaexcl;
 
  typename RtVectorX<nVars>::d x_old;              // old value of x
  typename RtVectorX<nIneqCon + nEqCon>::d u_old;  // old value of u
  typename RtVectorX<nIneqCon + nEqCon>::i A_old;  // old value of A
 
#ifdef OPTIMIZE_ADD_CONSTRAINT
  typename RtVectorX<nVars>::d T1;  // tmp vector
#endif
 
  int q;
 
  int iter;
 
  template <typename Scalar>
  inline Scalar distance(Scalar a, Scalar b) {
    Scalar a1, b1, t;
    a1 = std::abs(a);
    b1 = std::abs(b);
    if (a1 > b1) {
      t = (b1 / a1);
      return a1 * std::sqrt(1.0 + t * t);
    } else if (b1 > a1) {
      t = (a1 / b1);
      return b1 * std::sqrt(1.0 + t * t);
    }
    return a1 * std::sqrt(2.0);
  }
 
  inline void compute_d(typename RtVectorX<nVars>::d& d,
                        const typename RtMatrixX<nVars, nVars>::d& J,
                        const typename RtVectorX<nVars>::d& np) {
#ifdef OPTIMIZE_COMPUTE_D
    d.noalias() = J.adjoint() * np;
#else
    d = J.adjoint() * np;
#endif
  }
 
  inline void update_z(typename RtVectorX<nVars>::d& z,
                       const typename RtMatrixX<nVars, nVars>::d& J,
                       const typename RtVectorX<nVars>::d& d, int iq) {
#ifdef OPTIMIZE_UPDATE_Z
    z.noalias() = J.rightCols(nVars - iq) * d.tail(nVars - iq);
#else
    z = J.rightCols(J.cols() - iq) * d.tail(J.cols() - iq);
#endif
  }
 
  inline void update_r(const typename RtMatrixX<nVars, nVars>::d& R,
                       typename RtVectorX<nIneqCon + nEqCon>::d& r,
                       const typename RtVectorX<nVars>::d& d, int iq) {
    r.head(iq) = d.head(iq);
    R.topLeftCorner(iq, iq)
        .template triangularView<Eigen::Upper>()
        .solveInPlace(r.head(iq));
  }
 
  bool add_constraint(typename RtMatrixX<nVars, nVars>::d& R,
                      typename RtMatrixX<nVars, nVars>::d& J,
                      typename RtVectorX<nVars>::d& d, int& iq, double& R_norm);
 
  void delete_constraint(typename RtMatrixX<nVars, nVars>::d& R,
                         typename RtMatrixX<nVars, nVars>::d& J,
                         typename RtVectorX<nIneqCon + nEqCon>::i& A,
                         typename RtVectorX<nIneqCon + nEqCon>::d& u, int& iq,
                         int l);
};
 
} /* namespace solvers */
} /* namespace eiquadprog */
 
#include "eiquadprog/eiquadprog-rt.hxx"
/* --- Details
 * -------------------------------------------------------------------- */
 
#endif /* __eiquadprog_rt_hpp__ */