edge_interface.h

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/*********************************************************************
 *
 *  Software License Agreement
 *
 *  Copyright (c) 2020,
 *  TU Dortmund - Institute of Control Theory and Systems Engineering.
 *  All rights reserved.
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program 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 General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program.  If not, see <https://www.gnu.org/licenses/>.
 *
 *  Authors: Christoph Rösmann
 *********************************************************************/
 
#ifndef SRC_OPTIMIZATION_INCLUDE_CORBO_OPTIMIZATION_HYPER_GRAPH_EDGE_INTERFACE_H_
#define SRC_OPTIMIZATION_INCLUDE_CORBO_OPTIMIZATION_HYPER_GRAPH_EDGE_INTERFACE_H_
 
#include <corbo-core/types.h>
#include <corbo-optimization/hyper_graph/edge_cache.h>
 
#include <memory>
 
namespace corbo {
 
class VertexInterface;     // Forward declaration, include in subclass!
class VertexSetInterface;  // Forward declaration, include in subclass!
class EdgeSetInterface;    // Forward declaration for friend access
 
class EdgeInterface
{
    friend class EdgeSetInterface;
 
 public:
    using Ptr  = std::shared_ptr<EdgeInterface>;
    using UPtr = std::unique_ptr<EdgeInterface>;
 
    virtual ~EdgeInterface() {}
 
    virtual int getDimension() const = 0;
 
    virtual void computeValues(Eigen::Ref<Eigen::VectorXd> values) = 0;
 
    virtual double computeSumOfValues()
    {
        Eigen::VectorXd values(getDimension());
        computeValues(values);
        return values.sum();
    }
 
    virtual double computeSquaredNormOfValues()
    {
        Eigen::VectorXd values(getDimension());
        computeValues(values);
        return values.squaredNorm();
    }
 
    virtual int getNumVertices() const = 0;
    virtual int verticesDimension() const = 0;
 
    virtual VertexInterface* getVertexRaw(int idx)          = 0;
    virtual const VertexInterface* getVertex(int idx) const = 0;
 
    int getNumFiniteVerticesLowerBounds() const;
    int getNumFiniteVerticesUpperBounds() const;
};
 
class BaseEdge : public EdgeInterface
{
    friend class EdgeSetInterface;
 
 public:
    using Ptr  = std::shared_ptr<BaseEdge>;
    using UPtr = std::unique_ptr<BaseEdge>;
 
    int getDimension() const override = 0;
 
    virtual bool isLeastSquaresForm() const { return false; }
 
    virtual bool isLinear() const { return false; }
    virtual bool providesJacobian() const { return false; }
    virtual bool providesHessian() const { return false; }
 
    void computeValues(Eigen::Ref<Eigen::VectorXd> values) override = 0;
 
    virtual void computeJacobian(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> block_jacobian, const double* multipliers = nullptr);
 
    virtual void computeHessianInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                   Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
 
    virtual void computeHessian(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
 
    virtual void computeHessianInc(int vtx_idx_i, int vtx_idx_j, Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr,
                                   double weight = 1.0);
 
 
    void reserveCacheMemory(int num_value_vectors, int num_jacobians)
    {
        reserveValuesCacheMemory(num_value_vectors);
        reserveJacobiansCacheMemory(num_jacobians);
    }
    void reserveValuesCacheMemory(int num_value_vectors) { _cache.reserveMemoryValues(num_value_vectors); }
    void reserveJacobiansCacheMemory(int num_jacobians) { _cache.reserveMemoryJacobians(num_jacobians); }
 
    void computeValuesCached() { computeValues(_cache.pushValues(getDimension())); }
 
    void computeSquaredNormOfValuesCached() { _cache.pushValues(1)[0] = computeSquaredNormOfValues(); }
 
    EdgeCache& getCache() { return _cache; }
    const EdgeCache& getCache() const { return _cache; }
 
 
    int getEdgeIdx() const { return _edge_idx; }
 
 protected:
    int _edge_idx = 0;
    EdgeCache _cache;
};
 
class BaseMixedEdge : public EdgeInterface
{
    friend class EdgeSetInterface;
 
 public:
    using Ptr  = std::shared_ptr<BaseMixedEdge>;
    using UPtr = std::unique_ptr<BaseMixedEdge>;
 
    int getDimension() const override { return getObjectiveDimension() + getEqualityDimension() + getInequalityDimension(); }
 
    virtual int getObjectiveDimension() const  = 0;
    virtual int getEqualityDimension() const   = 0;
    virtual int getInequalityDimension() const = 0;
 
    virtual bool isObjectiveLeastSquaresForm() const = 0;
 
    virtual bool isObjectiveLinear() const { return false; }
    virtual bool isEqualityLinear() const { return false; }
    virtual bool isInequalityLinear() const { return false; }
 
    virtual void precompute()                                                     = 0;
    virtual void computeObjectiveValues(Eigen::Ref<Eigen::VectorXd> obj_values)   = 0;
    virtual void computeEqualityValues(Eigen::Ref<Eigen::VectorXd> eq_values)     = 0;
    virtual void computeInequalityValues(Eigen::Ref<Eigen::VectorXd> ineq_values) = 0;
 
    void computeValues(Eigen::Ref<Eigen::VectorXd> values) final
    {
        precompute();
        computeObjectiveValues(values);
        computeEqualityValues(values.segment(getObjectiveDimension(), getEqualityDimension()));
        computeInequalityValues(values.tail(getInequalityDimension()));
    }
 
    virtual double computeSumOfObjectiveValues()
    {
        Eigen::VectorXd values(getObjectiveDimension());
        computeObjectiveValues(values);
        return values.sum();
    }
 
    virtual double computeSquaredNormOfObjectiveValues()
    {
        Eigen::VectorXd values(getObjectiveDimension());
        computeObjectiveValues(values);
        return values.squaredNorm();
    }
 
    virtual void computeObjectiveJacobian(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> block_jacobian, const double* multipliers = nullptr);
    virtual void computeEqualityJacobian(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> block_jacobian, const double* multipliers = nullptr);
    virtual void computeInequalityJacobian(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> block_jacobian, const double* multipliers = nullptr);
    virtual void computeConstraintJacobians(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> eq_jacobian, Eigen::Ref<Eigen::MatrixXd> ineq_jacobian,
                                            const double* eq_multipliers = nullptr, const double* ineq_multipliers = nullptr);
    virtual void computeJacobians(int vtx_idx, Eigen::Ref<Eigen::MatrixXd> obj_jacobian, Eigen::Ref<Eigen::MatrixXd> eq_jacobian,
                                  Eigen::Ref<Eigen::MatrixXd> ineq_jacobian, const double* obj_multipliers = nullptr,
                                  const double* eq_multipliers = nullptr, const double* ineq_multipliers = nullptr);
 
    virtual void computeObjectiveHessian(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                         Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeEqualityHessian(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                        Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeInequalityHessian(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                          Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeHessians(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& obj_jacobian_i,
                                 const Eigen::Ref<const Eigen::MatrixXd>& eq_jacobian_i, const Eigen::Ref<const Eigen::MatrixXd>& ineq_jacobian_i,
                                 Eigen::Ref<Eigen::MatrixXd> obj_hessian_ij, Eigen::Ref<Eigen::MatrixXd> eq_hessian_ij,
                                 Eigen::Ref<Eigen::MatrixXd> ineq_hessian_ij, const double* multipliers_eq = nullptr,
                                 const double* multipliers_ineq = nullptr, double weight_obj = 1.0);
    virtual void computeConstraintHessians(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& eq_jacobian_i,
                                           const Eigen::Ref<const Eigen::MatrixXd>& ineq_jacobian_i, Eigen::Ref<Eigen::MatrixXd> eq_hessian_ij,
                                           Eigen::Ref<Eigen::MatrixXd> ineq_hessian_ij, const double* multipliers_eq = nullptr,
                                           const double* multipliers_ineq = nullptr);
 
    virtual void computeObjectiveHessianInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                            Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeEqualityHessianInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                           Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeInequalityHessianInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& block_jacobian_i,
                                             Eigen::Ref<Eigen::MatrixXd> block_hessian_ij, const double* multipliers = nullptr, double weight = 1.0);
    virtual void computeHessiansInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& obj_jacobian_i,
                                    const Eigen::Ref<const Eigen::MatrixXd>& eq_jacobian_i, const Eigen::Ref<const Eigen::MatrixXd>& ineq_jacobian_i,
                                    Eigen::Ref<Eigen::MatrixXd> obj_hessian_ij, Eigen::Ref<Eigen::MatrixXd> eq_hessian_ij,
                                    Eigen::Ref<Eigen::MatrixXd> ineq_hessian_ij, const double* multipliers_eq = nullptr,
                                    const double* multipliers_ineq = nullptr, double weight_obj = 1.0);
    virtual void computeConstraintHessiansInc(int vtx_idx_i, int vtx_idx_j, const Eigen::Ref<const Eigen::MatrixXd>& eq_jacobian_i,
                                              const Eigen::Ref<const Eigen::MatrixXd>& ineq_jacobian_i, Eigen::Ref<Eigen::MatrixXd> eq_hessian_ij,
                                              Eigen::Ref<Eigen::MatrixXd> ineq_hessian_ij, const double* multipliers_eq = nullptr,
                                              const double* multipliers_ineq = nullptr);
 
 
    void reserveCacheMemory(int num_value_vectors, int num_jacobians)
    {
        reserveValuesCacheMemory(num_value_vectors, num_value_vectors, num_value_vectors);
        reserveJacobiansCacheMemory(num_jacobians, num_jacobians, num_jacobians);
    }
    void reserveValuesCacheMemory(int num_obj_values, int num_eq_values, int num_ineq_values)
    {
        _objective_cache.reserveMemoryValues(num_obj_values);
        _equality_cache.reserveMemoryValues(num_eq_values);
        _inequality_cache.reserveMemoryValues(num_ineq_values);
    }
    void reserveJacobiansCacheMemory(int num_obj_jacobians, int num_eq_jacobians, int num_ineq_jacobians)
    {
        _objective_cache.reserveMemoryJacobians(num_obj_jacobians);
        _equality_cache.reserveMemoryJacobians(num_eq_jacobians);
        _inequality_cache.reserveMemoryJacobians(num_ineq_jacobians);
    }
 
    void computeObjectiveValuesCached() { computeObjectiveValues(_objective_cache.pushValues(getObjectiveDimension())); }
    void computeSquaredNormOfObjectiveValuesCached() { _objective_cache.pushValues(1)[0] = computeSquaredNormOfObjectiveValues(); }
    void computeEqualityValuesCached() { computeEqualityValues(_equality_cache.pushValues(getEqualityDimension())); }
    void computeInequalityValuesCached() { computeInequalityValues(_inequality_cache.pushValues(getInequalityDimension())); }
 
    EdgeCache& getObjectiveCache() { return _objective_cache; }
    const EdgeCache& getObjectiveCache() const { return _objective_cache; }
 
    EdgeCache& getEqualityCache() { return _equality_cache; }
    const EdgeCache& getEqualityCache() const { return _equality_cache; }
 
    EdgeCache& getInequalityCache() { return _inequality_cache; }
    const EdgeCache& getInequalityCache() const { return _inequality_cache; }
 
 
    int getEdgeObjectiveIdx() const { return _edge_idx_obj; }
    int getEdgeEqualityIdx() const { return _edge_idx_eq; }
    int getEdgeInequalityIdx() const { return _edge_idx_ineq; }
 
 protected:
    int _edge_idx_obj  = 0;
    int _edge_idx_eq   = 0;
    int _edge_idx_ineq = 0;
 
    EdgeCache _objective_cache;
    EdgeCache _equality_cache;
    EdgeCache _inequality_cache;
};
 
}  // namespace corbo
 
#endif  // SRC_OPTIMIZATION_INCLUDE_CORBO_OPTIMIZATION_HYPER_GRAPH_EDGE_INTERFACE_H_