/******************************************************************************

 * Top contributors (to current version):

 *   Tim King, Morgan Deters, Mathias Preiner

 *

 * This file is part of the cvc5 project.

 *

 * Copyright (c) 2009-2021 by the authors listed in the file AUTHORS

 * in the top-level source directory and their institutional affiliations.

 * All rights reserved.  See the file COPYING in the top-level source

 * directory for licensing information.

 * ****************************************************************************

 *

 * This is an implementation of the Simplex Module for the Simplex for

 * DPLL(T) decision procedure.

 *

 * This implements the Simplex module for the Simpelx for DPLL(T) decision

 * procedure.

 * See the Simplex for DPLL(T) technical report for more background.(citation?)

 * This shares with the theory a Tableau, and a PartialModel that:

 *  - satisfies the equalities in the Tableau, and

 *  - the assignment for the non-basic variables satisfies their bounds.

 * This is required to either produce a conflict or satisifying PartialModel.

 * Further, we require being told when a basic variable updates its value.

 *

 * During the Simplex search we maintain a queue of variables.

 * The queue is required to contain all of the basic variables that voilate

 * their bounds.

 * As elimination from the queue is more efficient to be done lazily,

 * we do not maintain that the queue of variables needs to be only basic

 * variables or only variables that satisfy their bounds.

 *

 * The simplex procedure roughly follows Alberto's thesis. (citation?)

 * There is one round of selecting using a heuristic pivoting rule.

 * (See PreferenceFunction Documentation for the available options.)

 * The non-basic variable is the one that appears in the fewest pivots.

 * (Bruno says that Leonardo invented this first.)

 * After this, Bland's pivot rule is invoked.

 *

 * During this proccess, we periodically inspect the queue of variables to

 * 1) remove now extraneous extries,

 * 2) detect conflicts that are "waiting" on the queue but may not be detected

 *    by the current queue heuristics, and

 * 3) detect multiple conflicts.

 *

 * Conflicts are greedily slackened to use the weakest bounds that still

 * produce the conflict.

 *

 * Extra things tracked atm: (Subject to change at Tim's whims)

 * - A superset of all of the newly pivoted variables.

 * - A queue of additional conflicts that were discovered by Simplex.

 *   These are theory valid and are currently turned into lemmas

 */

#include "cvc5_private.h"

#pragma once

#include "theory/arith/linear_equality.h"

#include "theory/arith/simplex.h"

#include "theory/arith/simplex_update.h"

#include "util/dense_map.h"

#include "util/statistics_stats.h"

namespace cvc5 {

namespace theory {

namespace arith {

public:

  SumOfInfeasibilitiesSPD(LinearEqualityModule& linEq, ErrorSet& errors, RaiseConflict conflictChannel, TempVarMalloc tvmalloc);

  Result::Sat findModel(bool exactResult) override;

  // other error variables are dropping

  WitnessImprovement dualLikeImproveError(ArithVar evar);

  WitnessImprovement primalImproveError(ArithVar evar);

private:

  /** The current sum of infeasibilities variable. */

  ArithVar d_soiVar;

  // dual like

  // - found conflict

  // - satisfied error set

  Result::Sat sumOfInfeasibilities();

  // static const uint32_t PENALTY = 4;

  // DenseMultiset d_scores;

  // void decreasePenalties(){ d_scores.removeOneOfEverything(); }

  // uint32_t penalty(ArithVar x) const { return d_scores.count(x); }

  // void setPenalty(ArithVar x, WitnessImprovement w){

  //   if(improvement(w)){

  //     if(d_scores.count(x) > 0){

  //       d_scores.removeAll(x);

  //     }

  //   }else{

  //     d_scores.setCount(x, PENALTY);

  //   }

  // }

  int32_t d_pivotBudget;

  // enum PivotImprovement {

  //   ErrorDropped,

  //   NonDegenerate,

  //   HeuristicDegenerate,

  //   BlandsDegenerate

  // };

  WitnessImprovement d_prevWitnessImprovement;

  uint32_t d_witnessImprovementInARow;

  uint32_t degeneratePivotsInARow() const;

  static const uint32_t s_focusThreshold = 6;

  static const uint32_t s_maxDegeneratePivotsBeforeBlandsOnLeaving = 100;

  static const uint32_t s_maxDegeneratePivotsBeforeBlandsOnEntering = 10;

  DenseMap<uint32_t> d_leavingCountSinceImprovement;

    }else{

    }

    } else {

    }

  }

  bool debugSOI(WitnessImprovement w, std::ostream& out, int instance) const;

  void debugPrintSignal(ArithVar updated) const;

  ArithVarVec d_sgnDisagreements;

  void logPivot(WitnessImprovement w);

  void updateAndSignal(const UpdateInfo& selected, WitnessImprovement w);

  UpdateInfo selectUpdate(LinearEqualityModule::UpdatePreferenceFunction upf,

                          LinearEqualityModule::VarPreferenceFunction bpf);

  // UpdateInfo selectUpdateForDualLike(ArithVar basic){

  //   TimerStat::CodeTimer codeTimer(d_statistics.d_selectUpdateForDualLike);

  //   LinearEqualityModule::UpdatePreferenceFunction upf =

  //     &LinearEqualityModule::preferWitness<true>;

  //   LinearEqualityModule::VarPreferenceFunction bpf =

  //     &LinearEqualityModule::minVarOrder;

  //   return selectPrimalUpdate(basic, upf, bpf);

  // }

  // UpdateInfo selectUpdateForPrimal(ArithVar basic, bool useBlands){

  //   TimerStat::CodeTimer codeTimer(d_statistics.d_selectUpdateForPrimal);

  //   LinearEqualityModule::UpdatePreferenceFunction upf = useBlands ?

  //     &LinearEqualityModule::preferWitness<false>:

  //     &LinearEqualityModule::preferWitness<true>;

  //   LinearEqualityModule::VarPreferenceFunction bpf = useBlands ?

  //     &LinearEqualityModule::minVarOrder :

  //     &LinearEqualityModule::minRowLength;

  //   bpf = &LinearEqualityModule::minVarOrder;

  //   return selectPrimalUpdate(basic, upf, bpf);

  // }

  // WitnessImprovement selectFocusImproving() ;

  WitnessImprovement soiRound();

  WitnessImprovement SOIConflict();

  std::vector< ArithVarVec > greedyConflictSubsets();

  bool generateSOIConflict(const ArithVarVec& subset);

  // WitnessImprovement focusUsingSignDisagreements(ArithVar basic);

  // WitnessImprovement focusDownToLastHalf();

  // WitnessImprovement adjustFocusShrank(const ArithVarVec& drop);

  // WitnessImprovement focusDownToJust(ArithVar v);

  void adjustFocusAndError(const UpdateInfo& up, const AVIntPairVec& focusChanges);

  /**

   * This is the main simplex for DPLL(T) loop.

   * It runs for at most maxIterations.

   *

   * Returns true iff it has found a conflict.

   * d_conflictVariable will be set and the conflict for this row is reported.

   */

  bool searchForFeasibleSolution(uint32_t maxIterations);

  }

  void quickExplain();

  DenseSet d_qeInSoi;

  DenseSet d_qeInUAndNotInSoi;

  ArithVarVec d_qeConflict;

  ArithVarVec d_qeGreedyOrder;

  sgn_table d_qeSgns;

  uint32_t quickExplainRec(uint32_t cEnd, uint32_t uEnd);

  void qeAddRange(uint32_t begin, uint32_t end);

  void qeRemoveRange(uint32_t begin, uint32_t end);

  void qeSwapRange(uint32_t N, uint32_t r, uint32_t s);

  unsigned trySet(const ArithVarVec& set);

  unsigned tryAllSubsets(const ArithVarVec& set, unsigned depth, ArithVarVec& tmp);

  /** These fields are designed to be accessible to TheoryArith methods. */

  public:

    TimerStat d_initialSignalsTime;

    IntStat d_initialConflicts;

    IntStat d_soiFoundUnsat;

    IntStat d_soiFoundSat;

    IntStat d_soiMissed;

    IntStat d_soiConflicts;

    IntStat d_hasToBeMinimal;

    IntStat d_maybeNotMinimal;

    TimerStat d_soiTimer;

    TimerStat d_soiFocusConstructionTimer;

    TimerStat d_soiConflictMinimization;

    TimerStat d_selectUpdateForSOI;

    ReferenceStat<uint32_t> d_finalCheckPivotCounter;

    Statistics(const std::string& name, uint32_t& pivots);

  } d_statistics;

};/* class FCSimplexDecisionProcedure */

}  // namespace arith

}  // namespace theory

}  // namespace cvc5