#ifndef STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAQUERY_H_
#define STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAQUERY_H_

#include "storm/modelchecker/results/CheckResult.h"
#include "storm/modelchecker/multiobjective/SparseMultiObjectivePreprocessorResult.h"
#include "storm/modelchecker/multiobjective/pcaa/PcaaWeightVectorChecker.h"
#include "storm/storage/geometry/Polytope.h"

namespace storm {

    class Environment;
    
    namespace modelchecker {
        namespace multiobjective {
            
            /*
             * This class represents a query for the Pareto curve approximation algorithm (Pcaa).
             * It implements the necessary computations for the different query types.
             */
            template <class SparseModelType, typename GeometryValueType>
            class SparsePcaaQuery {
            public:
                
                // Typedefs for simple geometric objects
                typedef std::vector<GeometryValueType> Point;
                typedef std::vector<GeometryValueType> WeightVector;
                
                virtual ~SparsePcaaQuery() = default;
                
                /*
                 * Invokes the computation and retrieves the result
                 */
                virtual std::unique_ptr<CheckResult> check(Environment const& env) = 0;
                
                /*
                 * Exports the current approximations and the currently processed points into respective .csv files located at the given directory.
                 * The polytopes are represented as the set of vertices. 
                 * Note that the approximations will be intersected with a  (sufficiently large) hyperrectangle in order to ensure that the polytopes are bounded
                 * This only works for 2 dimensional queries.
                 */
                void exportPlotOfCurrentApproximation(Environment const& env) const;
                
            protected:
                
                /*
                 * Represents the information obtained in a single iteration of the algorithm
                 */
                struct RefinementStep {
                    WeightVector weightVector;
                    Point lowerBoundPoint;
                    Point upperBoundPoint;
                };
                
                /* 
                 * Creates a new query for the Pareto curve approximation algorithm (Pcaa)
                 * @param preprocessorResult the result from preprocessing
                 */
                SparsePcaaQuery(SparseMultiObjectivePreprocessorResult<SparseModelType>& preprocessorResult);
                
                /*
                 * Returns a weight vector w that separates the under approximation from the given point p, i.e.,
                 * For each x in the under approximation, it holds that w*x <= w*p
                 *
                 * @param pointToBeSeparated the point that is to be seperated
                 */
                WeightVector findSeparatingVector(Point const& pointToBeSeparated);

                /*
                 * Refines the current result w.r.t. the given direction vector.
                 */
                void performRefinementStep(Environment const& env, WeightVector&& direction);
                
                /*
                 * Updates the overapproximation after a refinement step has been performed
                 *
                 * @note The last entry of this->refinementSteps should be the newest step whose information is not yet included in the approximation.
                 */
                void updateOverApproximation();
                
                /*
                 * Updates the underapproximation after a refinement step has been performed
                 *
                 * @note The last entry of this->refinementSteps should be the newest step whose information is not yet included in the approximation.
                 */
                void updateUnderApproximation();
                
                /*
                 * Returns true iff the maximum number of refinement steps (as possibly specified in the settings) has been reached
                 */
                bool maxStepsPerformed(Environment const& env) const;
                
                /*
                 * Transforms the given point (or polytope) to values w.r.t. the original model/formula (e.g. negates values for minimizing objectives).
                 */
                Point transformPointToOriginalModel(Point const& polytope) const;
                std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> transformPolytopeToOriginalModel(std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> const& polytope) const;

                
                SparseModelType const& originalModel;
                storm::logic::MultiObjectiveFormula const& originalFormula;
                
                std::vector<Objective<typename SparseModelType::ValueType>> objectives;
                
                // The corresponding weight vector checker
                std::unique_ptr<PcaaWeightVectorChecker<SparseModelType>> weightVectorChecker;

                //The results in each iteration of the algorithm
                std::vector<RefinementStep> refinementSteps;
                //Overapproximation of the set of achievable values
                std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> overApproximation;
                //Underapproximation of the set of achievable values
                std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> underApproximation;
                
                 // stores for each objective whether it still makes sense to check for this objective individually (i.e., with weight vector given by w_{i}>0 iff i=objIndex )
                storm::storage::BitVector diracWeightVectorsToBeChecked;
                
                
            };
            
        }
    }
}

#endif /* STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAQUERY_H_ */