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/*               This file is part of the program and library                */
/*    PaPILO --- Parallel Presolve for Integer and Linear Optimization       */
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/* Copyright (C) 2020-2026 Zuse Institute Berlin (ZIB)                       */
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#ifndef _PAPILO_CORE_PRIMAL_DUAL_SOL_VALIDATION_HPP_
#define _PAPILO_CORE_PRIMAL_DUAL_SOL_VALIDATION_HPP_

#include "papilo/core/Solution.hpp"
#include "papilo/core/postsolve/PostsolveStatus.hpp"

namespace papilo
{
template <typename REAL>
class PrimalDualSolValidation
{

 public:
   PrimalDualSolValidation( const Message msg, const Num<REAL> num_ )
       : num( num_ ), message( msg )
   {
   }

 private:
   Num<REAL> num;
   Message message{};

 private:

   bool
   checkLength( const Solution<REAL>& solution, const Problem<REAL>& problem )
   {
      const int nCols = problem.getNCols();

      bool primal_check = (int) solution.primal.size() != nCols;
      if( solution.type == SolutionType::kPrimalDual )
         return primal_check || (int) solution.reducedCosts.size() != nCols ||
                (int) solution.dual.size() != problem.getNRows();
      return primal_check;
   }

   bool
   checkPrimalBounds( const Vec<REAL>& primalSolution,
                      const Problem<REAL>& problem )
   {
      bool failure = false;

      const Vec<REAL>& ub = problem.getUpperBounds();
      const Vec<REAL>& lb = problem.getLowerBounds();

      for( int col = 0; col < problem.getNCols(); col++ )
      {
         if( problem.getColFlags()[col].test( ColFlag::kInactive ) )
            continue;

         if( ( ! problem.getColFlags()[col].test( ColFlag::kLbInf ) ) &&
             num.isFeasLT( primalSolution[col], lb[col] ) )
         {
            message.info( "Column {:<3} violates lower column bound () ({} ! >= {}).\n", col, (double) primalSolution[col], (double) lb[col]  );
            failure = true;
         }

         if( ( ! problem.getColFlags()[col].test( ColFlag::kUbInf ) ) &&
             num.isFeasGT( primalSolution[col], ub[col] ) )
         {
            message.info( "Column {:<3} violates upper column bound ({} ! <= {}).\n", col, (double) primalSolution[col], (double) ub[col]  );
            failure = true;
         }
      }
      return failure;
   }

   bool
   checkPrimalConstraintAndUpdateSlack( Solution<REAL>& solution,
                                        const Problem<REAL>& problem ) const
   {
      const Vec<REAL>& rhs = problem.getConstraintMatrix().getRightHandSides();
      const Vec<REAL>& lhs = problem.getConstraintMatrix().getLeftHandSides();

      if(solution.type == SolutionType::kPrimalDual)
      {
         solution.slack.clear();
         solution.slack.resize(problem.getNRows());
      }

      for( int row = 0; row < problem.getNRows(); row++ )
      {
         if( problem.getRowFlags()[row].test( RowFlag::kRedundant ) )
            continue;

         REAL rowValue = 0;
         auto entries = problem.getConstraintMatrix().getRowCoefficients( row );
         for( int j = 0; j < entries.getLength(); j++ )
         {
            int col = entries.getIndices()[j];
            if( problem.getColFlags()[col].test( ColFlag::kInactive ) )
               continue;
            REAL x = entries.getValues()[j];
            REAL primal = solution.primal[col];
            rowValue += x * primal;
         }

         bool lhs_inf = problem.getRowFlags()[row].test( RowFlag::kLhsInf );
         if( ( ! lhs_inf ) && num.isFeasLT( rowValue, lhs[row] ) )
         {
            message.info( "Row {:<3} violates row bounds ({:<3} < {:<3}).\n",
                          row, (double) lhs[row], (double) rowValue );
            return true;
         }
         bool rhs_inf = problem.getRowFlags()[row].test( RowFlag::kRhsInf );
         if( ( ! rhs_inf ) && num.isFeasGT( rowValue, rhs[row] ) )
         {
            message.info( "Row {:<3} violates row bounds ({:<3} < {:<3}).\n",
                          row, (double) rowValue, (double) rhs[row] );
            return true;
         }
         if(solution.type == SolutionType::kPrimalDual)
            solution.slack[row] = num.isFeasZero( rowValue ) ? 0 : rowValue;
      }
      return false;
   }

   bool
   checkPrimalFeasibilityAndUpdateSlack( Solution<REAL>& solution,
                                         const Problem<REAL>& problem )
   {
      bool primalBounds = checkPrimalBounds( solution.primal, problem );
      bool primalConstraint =
          checkPrimalConstraintAndUpdateSlack( solution, problem );
      return primalBounds || primalConstraint;
   }

   bool
   checkDualFeasibility( const Vec<REAL>& primalSolution,
                         const Vec<REAL>& dualSolution,
                         const Vec<REAL>& reducedCosts,
                         const Vec<VarBasisStatus>& basis,
                         const Problem<REAL>& problem )
   {
      const Vec<REAL> rhs = problem.getConstraintMatrix().getRightHandSides();
      const Vec<REAL> lhs = problem.getConstraintMatrix().getLeftHandSides();

      for( int variable = 0; variable < problem.getNCols(); variable++ )
      {
         if( problem.getColFlags()[variable].test( ColFlag::kInactive ) )
            continue;
         StableSum<REAL> colValue;

         auto coeff =
             problem.getConstraintMatrix().getColumnCoefficients( variable );
         for( int counter = 0; counter < coeff.getLength(); counter++ )
         {
            REAL value = coeff.getValues()[counter];
            int rowIndex = coeff.getIndices()[counter];
            colValue.add(dualSolution[rowIndex] * value);
         }

         if( ! num.isFeasEq( colValue.get() + reducedCosts[variable],
                           problem.getObjective().coefficients[variable] ) )
         {
            message.info(
                "Dual row {:<3} violates dual row bounds ({:<3} != {:<3}).\n",
                variable, (double)( colValue.get() + reducedCosts[variable] ),
                (double)problem.getObjective().coefficients[variable] );
            return true;
         }
      }
      return false;
   }

   bool
   checkComplementarySlackness( const Vec<REAL>& primalSolution,
                                const Vec<REAL>& dualSolution,
                                const Vec<REAL>& reducedCosts,
                                const Problem<REAL>& problem )

   {

      const Vec<REAL> lb = problem.getLowerBounds();
      const Vec<REAL> ub = problem.getUpperBounds();

      const Vec<REAL> rhs = problem.getConstraintMatrix().getRightHandSides();
      const Vec<REAL> lhs = problem.getConstraintMatrix().getLeftHandSides();
      for( int row = 0; row < problem.getNRows(); row++ )
      {
         if( problem.getRowFlags()[row].test( RowFlag::kRedundant ) )
            continue;

         REAL rowValue = 0;
         auto entries = problem.getConstraintMatrix().getRowCoefficients( row );
         for( int j = 0; j < entries.getLength(); j++ )
         {
            int col = entries.getIndices()[j];
            if( problem.getColFlags()[col].test( ColFlag::kFixed ) )
               continue;
            rowValue += entries.getValues()[j] * primalSolution[col];
         }

         if( ! problem.getRowFlags()[row].test( RowFlag::kLhsInf ) &&
             ! problem.getRowFlags()[row].test( RowFlag::kRhsInf ) )
         {
            if( num.isFeasGT( lhs[row], rowValue ) &&
                num.isFeasLT( rhs[row], rowValue ) &&
                ! num.isFeasZero( dualSolution[row] ) )
               return true;
         }
         else if( ! problem.getRowFlags()[row].test( RowFlag::kLhsInf ) )
         {
            assert( problem.getRowFlags()[row].test( RowFlag::kRhsInf ) );
            if( num.isFeasGT( lhs[row], rowValue ) &&
                ! num.isFeasZero( dualSolution[row] ) )
               return true;
         }
         else if( ( ! problem.getRowFlags()[row].test( RowFlag::kLhsInf ) ) &&
                  num.isFeasGT( rowValue, lhs[row] ) )
         {
            assert( problem.getRowFlags()[row].test( RowFlag::kRhsInf ) );
            if( num.isFeasLT( rhs[row], rowValue ) &&
                ! num.isFeasZero( dualSolution[row] ) )
               return true;
         }
      }

      for( int col = 0; col < problem.getNCols(); col++ )
      {
         if( problem.getColFlags()[col].test( ColFlag::kInactive ) )
            continue;

         bool isLbInf = problem.getColFlags()[col].test( ColFlag::kLbInf );
         bool isUbInf = problem.getColFlags()[col].test( ColFlag::kUbInf );
         REAL upperBound = ub[col];
         REAL lowerBound = lb[col];
         REAL reducedCost = reducedCosts[col];
         REAL sol = primalSolution[col];

         if( num.isFeasEq( upperBound, lowerBound ) && ! isLbInf &&
             ! isUbInf )
            continue;

         if( ! isLbInf && ! isUbInf )
         {
            if( num.isFeasGT( sol, lowerBound ) && num.isFeasLT( sol, upperBound ) &&
                ! num.isFeasZero( reducedCost ) )
               return true;
         }
         else if( ! isLbInf )
         {
            assert( isUbInf );
            if( num.isFeasGT( sol, lowerBound ) && ! num.isFeasZero( reducedCost ) )
               return true;
         }
         else if( ! isUbInf )
         {
            assert( isLbInf );
            if( num.isFeasLT( sol, upperBound ) && ! num.isFeasZero( reducedCost ) )
               return true;
         }
      }
      return false;
   }

   bool
   checkBasis( const Solution<REAL>& solution, const Problem<REAL>& problem )
   {
      if(! solution.basisAvailabe)
         return false;
      int number_basic_variable = 0;
      int number_rows = 0;
      for( int variable = 0; variable < problem.getNCols(); variable++ )
      {
         if( problem.getColFlags()[variable].test( ColFlag::kInactive ) )
            continue;
         bool ub_infinity =
             problem.getColFlags()[variable].test( ColFlag::kUbInf );
         bool lb_infinity =
             problem.getColFlags()[variable].test( ColFlag::kLbInf );
         REAL lb = problem.getLowerBounds()[variable];
         REAL ub = problem.getUpperBounds()[variable];
         REAL sol = solution.primal[variable];

         assert( ub_infinity || lb_infinity || num.isFeasGE( ub, lb ) );
         switch( solution.varBasisStatus[variable] )
         {
         case VarBasisStatus::BASIC:
            if( ! num.isFeasZero( solution.reducedCosts[variable] ) )
               return true;
            number_basic_variable++;
            break;
         case VarBasisStatus::FIXED:
            if( ub_infinity || lb_infinity || ! num.isFeasEq( lb, ub ) ||
                ! num.isFeasEq( sol, ub ) )
               return true;
            break;
         case VarBasisStatus::ON_LOWER:
            if( lb_infinity || ! num.isFeasEq( sol, lb ) )
               return true;
            break;
         case VarBasisStatus::ON_UPPER:
            if( ub_infinity || ! num.isFeasEq( sol, ub ) )
               return true;
            break;
         case VarBasisStatus::ZERO:
            if( ! lb_infinity || ! ub_infinity ||
                ! num.isFeasZero( sol ) )
               return true;
            break;
         case VarBasisStatus::UNDEFINED:
            return true;
         }
      }
      for( int row = 0; row < problem.getNRows(); row++ )
      {
         if( problem.getRowFlags()[row].test( RowFlag::kRedundant ) )
            continue;
         number_rows++;
         bool lhs_infinity =
             problem.getRowFlags()[row].test( RowFlag::kLhsInf );
         bool rhs_infinity =
             problem.getRowFlags()[row].test( RowFlag::kRhsInf );

         REAL lhs = problem.getConstraintMatrix().getLeftHandSides()[row];
         REAL rhs = problem.getConstraintMatrix().getRightHandSides()[row];
         REAL slack = solution.slack[row];

         assert( lhs_infinity || rhs_infinity || num.isFeasGE( rhs, lhs ) );
         switch( solution.rowBasisStatus[row] )
         {
         case VarBasisStatus::BASIC:
            if( ! num.isFeasZero( solution.dual[row] ) )
               return true;
            number_basic_variable++;
            break;
         case VarBasisStatus::FIXED:
            if( lhs_infinity || rhs_infinity || ! num.isFeasEq( lhs, rhs ) ||
                ! num.isFeasEq( slack, rhs ) )
               return true;
            assert( problem.getRowFlags()[row].test( RowFlag::kEquation ) );
            break;
         case VarBasisStatus::ON_LOWER:
            if( lhs_infinity || ! num.isFeasEq( slack, lhs ) )
               return true;
            break;
         case VarBasisStatus::ON_UPPER:
            if( rhs_infinity || ! num.isFeasEq( slack, rhs ) )
               return true;
            break;
         case VarBasisStatus::ZERO:
            if( ! rhs_infinity || ! lhs_infinity ||
                ! num.isFeasZero( slack ) )
               return true;
            break;
         case VarBasisStatus::UNDEFINED:
            return true;
         }
      }
      return number_basic_variable != number_rows;
   }

 public:
   bool
   checkObjectiveFunction( const Vec<REAL>& primalSolution,
                           const Vec<REAL>& dualSolution,
                           const Vec<REAL>& reducedCosts,
                           const Problem<REAL>& problem )
   {
      REAL duality_gap =
          getDualityGap( primalSolution, dualSolution, reducedCosts, problem );
      return ! num.isFeasZero( duality_gap )  ;
   }

   PostsolveStatus
   verifySolutionAndUpdateSlack( Solution<REAL>& solution,
                                 const Problem<REAL>& problem )
   {

      bool failure = checkLength( solution, problem );
      if( failure )
      {
         message.info( "Solution vector length check FAILED.\n" );
         return PostsolveStatus::kFailed;
      }

      failure = checkPrimalFeasibilityAndUpdateSlack( solution, problem );
      if( failure )
      {
         message.info( "Primal feasibility check FAILED.\n" );
         return PostsolveStatus::kFailed;
      }

      if( solution.type == SolutionType::kPrimalDual )
      {
         if( checkDualFeasibility( solution.primal, solution.dual,
                                   solution.reducedCosts,
                                   solution.varBasisStatus, problem ) )
         {
            message.info( "Dual feasibility check FAILED.\n" );
            failure = true;
         }

         if( checkComplementarySlackness( solution.primal, solution.dual,
                                          solution.reducedCosts, problem ) )
         {
            message.info( "Complementary slack check FAILED.\n" );
            failure = true;
         }

         if( checkBasis( solution, problem ) )
         {
            message.info( "Basis check FAILED.\n" );
            failure = true;
         }

         if( checkObjectiveFunction( solution.primal, solution.dual,
                                     solution.reducedCosts, problem ) )
         {
            message.info( "Objective function failed.\n" );
         }
         if( failure )
            return PostsolveStatus::kFailed;
      }

      message.info( "Solution passed validation\n" );
      return PostsolveStatus::kOk;
   }

   REAL
   getDualityGap( const Vec<REAL>& primalSolution,
                  const Vec<REAL>& dualSolution, const Vec<REAL>& reducedCosts,
                  const Problem<REAL>& problem )
   {
      StableSum<REAL> primal_objective;
      for( int i = 0; i < problem.getNCols(); i++ )
      {
         primal_objective.add( primalSolution[i] *
                               problem.getObjective().coefficients[i] );
      }
      StableSum<REAL> dual_objective;
      for( int i = 0; i < problem.getNRows(); i++ )
      {
         REAL dual = dualSolution[i];
         REAL side;
         if( dual < 0 )
            side = problem.getConstraintMatrix().getRightHandSides()[i];
         else
            side = problem.getConstraintMatrix().getLeftHandSides()[i];
         dual_objective.add( dual * side );
      }
      for( int i = 0; i < problem.getNCols(); i++ )
      {
         REAL reducedCost = reducedCosts[i];
         REAL side;
         if( reducedCost < 0 )
            side = problem.getUpperBounds()[i];
         else
            side = problem.getLowerBounds()[i];
         dual_objective.add( reducedCost * side );
      }
      return primal_objective.get() - dual_objective.get();
   }
};
} // namespace papilo

#endif
