https://github.com/audemard/glucose
Tip revision: 1a349a88a41addc71df0a56d5379914b7d6b2b9b authored by audemard on 09 May 2023, 12:58:23 UTC
Glucose 4.1
Glucose 4.1
Tip revision: 1a349a8
Solver.h
/***************************************************************************************[Solver.h]
Glucose -- Copyright (c) 2009-2014, Gilles Audemard, Laurent Simon
CRIL - Univ. Artois, France
LRI - Univ. Paris Sud, France (2009-2013)
Labri - Univ. Bordeaux, France
Syrup (Glucose Parallel) -- Copyright (c) 2013-2014, Gilles Audemard, Laurent Simon
CRIL - Univ. Artois, France
Labri - Univ. Bordeaux, France
Glucose sources are based on MiniSat (see below MiniSat copyrights). Permissions and copyrights of
Glucose (sources until 2013, Glucose 3.0, single core) are exactly the same as Minisat on which it
is based on. (see below).
Glucose-Syrup sources are based on another copyright. Permissions and copyrights for the parallel
version of Glucose-Syrup (the "Software") are granted, free of charge, to deal with the Software
without restriction, including the rights to use, copy, modify, merge, publish, distribute,
sublicence, and/or sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
- The above and below copyrights notices and this permission notice shall be included in all
copies or substantial portions of the Software;
- The parallel version of Glucose (all files modified since Glucose 3.0 releases, 2013) cannot
be used in any competitive event (sat competitions/evaluations) without the express permission of
the authors (Gilles Audemard / Laurent Simon). This is also the case for any competitive event
using Glucose Parallel as an embedded SAT engine (single core or not).
--------------- Original Minisat Copyrights
Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
Copyright (c) 2007-2010, Niklas Sorensson
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
associated documentation files (the "Software"), to deal in the Software without restriction,
including without limitation the rights to use, copy, modify, merge, publish, distribute,
sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or
substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT
OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
**************************************************************************************************/
#ifndef Glucose_Solver_h
#define Glucose_Solver_h
#include "mtl/Heap.h"
#include "mtl/Alg.h"
#include "utils/Options.h"
#include "core/SolverTypes.h"
#include "core/BoundedQueue.h"
#include "core/Constants.h"
#include "mtl/Clone.h"
#include "core/SolverStats.h"
namespace Glucose {
// Core stats
enum CoreStats {
sumResSeen,
sumRes,
sumTrail,
nbPromoted,
originalClausesSeen,
sumDecisionLevels,
nbPermanentLearnts,
nbRemovedClauses,
nbRemovedUnaryWatchedClauses,
nbReducedClauses,
nbDL2,
nbBin,
nbUn,
nbReduceDB,
rnd_decisions,
nbstopsrestarts,
nbstopsrestartssame,
lastblockatrestart,
dec_vars,
clauses_literals,
learnts_literals,
max_literals,
tot_literals,
noDecisionConflict
} ;
#define coreStatsSize 24
//=================================================================================================
// Solver -- the main class:
class Solver : public Clone {
friend class SolverConfiguration;
public:
// Constructor/Destructor:
//
Solver();
Solver(const Solver &s);
virtual ~Solver();
/**
* Clone function
*/
virtual Clone* clone() const {
return new Solver(*this);
}
// Problem specification:
//
virtual Var newVar (bool polarity = true, bool dvar = true); // Add a new variable with parameters specifying variable mode.
bool addClause (const vec<Lit>& ps); // Add a clause to the solver.
bool addEmptyClause(); // Add the empty clause, making the solver contradictory.
bool addClause (Lit p); // Add a unit clause to the solver.
bool addClause (Lit p, Lit q); // Add a binary clause to the solver.
bool addClause (Lit p, Lit q, Lit r); // Add a ternary clause to the solver.
virtual bool addClause_( vec<Lit>& ps); // Add a clause to the solver without making superflous internal copy. Will
// change the passed vector 'ps'.
// Solving:
//
bool simplify (); // Removes already satisfied clauses.
bool solve (const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions.
lbool solveLimited (const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions (With resource constraints).
bool solve (); // Search without assumptions.
bool solve (Lit p); // Search for a model that respects a single assumption.
bool solve (Lit p, Lit q); // Search for a model that respects two assumptions.
bool solve (Lit p, Lit q, Lit r); // Search for a model that respects three assumptions.
bool okay () const; // FALSE means solver is in a conflicting state
// Convenience versions of 'toDimacs()':
void toDimacs (FILE* f, const vec<Lit>& assumps); // Write CNF to file in DIMACS-format.
void toDimacs (const char *file, const vec<Lit>& assumps);
void toDimacs (FILE* f, Clause& c, vec<Var>& map, Var& max);
void toDimacs (const char* file);
void toDimacs (const char* file, Lit p);
void toDimacs (const char* file, Lit p, Lit q);
void toDimacs (const char* file, Lit p, Lit q, Lit r);
// Display clauses and literals
void printLit(Lit l);
void printClause(CRef c);
void printInitialClause(CRef c);
// Variable mode:
//
void setPolarity (Var v, bool b); // Declare which polarity the decision heuristic should use for a variable. Requires mode 'polarity_user'.
void setDecisionVar (Var v, bool b); // Declare if a variable should be eligible for selection in the decision heuristic.
// Read state:
//
lbool value (Var x) const; // The current value of a variable.
lbool value (Lit p) const; // The current value of a literal.
lbool modelValue (Var x) const; // The value of a variable in the last model. The last call to solve must have been satisfiable.
lbool modelValue (Lit p) const; // The value of a literal in the last model. The last call to solve must have been satisfiable.
int nAssigns () const; // The current number of assigned literals.
int nClauses () const; // The current number of original clauses.
int nLearnts () const; // The current number of learnt clauses.
int nVars () const; // The current number of variables.
int nFreeVars () ;
inline char valuePhase(Var v) {return polarity[v];}
// Incremental mode
void setIncrementalMode();
void initNbInitialVars(int nb);
void printIncrementalStats();
bool isIncremental();
// Resource contraints:
//
void setConfBudget(int64_t x);
void setPropBudget(int64_t x);
void budgetOff();
void interrupt(); // Trigger a (potentially asynchronous) interruption of the solver.
void clearInterrupt(); // Clear interrupt indicator flag.
// Memory managment:
//
virtual void garbageCollect();
void checkGarbage(double gf);
void checkGarbage();
// Extra results: (read-only member variable)
//
vec<lbool> model; // If problem is satisfiable, this vector contains the model (if any).
vec<Lit> conflict; // If problem is unsatisfiable (possibly under assumptions),
// this vector represent the final conflict clause expressed in the assumptions.
// Mode of operation:
//
int verbosity;
int verbEveryConflicts;
int showModel;
// Constants For restarts
double K;
double R;
double sizeLBDQueue;
double sizeTrailQueue;
// Constants for reduce DB
int firstReduceDB;
int incReduceDB;
int specialIncReduceDB;
unsigned int lbLBDFrozenClause;
bool chanseokStrategy;
int coLBDBound; // Keep all learnts with lbd<=coLBDBound
// Constant for reducing clause
int lbSizeMinimizingClause;
unsigned int lbLBDMinimizingClause;
// Constant for heuristic
double var_decay;
double max_var_decay;
double clause_decay;
double random_var_freq;
double random_seed;
int ccmin_mode; // Controls conflict clause minimization (0=none, 1=basic, 2=deep).
int phase_saving; // Controls the level of phase saving (0=none, 1=limited, 2=full).
bool rnd_pol; // Use random polarities for branching heuristics.
bool rnd_init_act; // Initialize variable activities with a small random value.
bool randomizeFirstDescent; // the first decisions (until first cnflict) are made randomly
// Useful for syrup!
// Constant for Memory managment
double garbage_frac; // The fraction of wasted memory allowed before a garbage collection is triggered.
// Certified UNSAT ( Thanks to Marijn Heule
// New in 2016 : proof in DRAT format, possibility to use binary output
FILE* certifiedOutput;
bool certifiedUNSAT;
bool vbyte;
void write_char (unsigned char c);
void write_lit (int n);
// Panic mode.
// Save memory
uint32_t panicModeLastRemoved, panicModeLastRemovedShared;
bool useUnaryWatched; // Enable unary watched literals
bool promoteOneWatchedClause; // One watched clauses are promotted to two watched clauses if found empty
// Functions useful for multithread solving
// Useless in the sequential case
// Overide in ParallelSolver
virtual void parallelImportClauseDuringConflictAnalysis(Clause &c,CRef confl);
virtual bool parallelImportClauses(); // true if the empty clause was received
virtual void parallelImportUnaryClauses();
virtual void parallelExportUnaryClause(Lit p);
virtual void parallelExportClauseDuringSearch(Clause &c);
virtual bool parallelJobIsFinished();
virtual bool panicModeIsEnabled();
double luby(double y, int x);
// Statistics
vec<uint64_t> stats;
// Important stats completely related to search. Keep here
uint64_t solves,starts,decisions,propagations,conflicts,conflictsRestarts;
protected:
long curRestart;
// Alpha variables
bool glureduce;
uint32_t restart_inc;
bool luby_restart;
bool adaptStrategies;
uint32_t luby_restart_factor;
bool randomize_on_restarts, fixed_randomize_on_restarts, newDescent;
uint32_t randomDescentAssignments;
bool forceUnsatOnNewDescent;
// Helper structures:
//
struct VarData { CRef reason; int level; };
static inline VarData mkVarData(CRef cr, int l){ VarData d = {cr, l}; return d; }
struct Watcher {
CRef cref;
Lit blocker;
Watcher(CRef cr, Lit p) : cref(cr), blocker(p) {}
bool operator==(const Watcher& w) const { return cref == w.cref; }
bool operator!=(const Watcher& w) const { return cref != w.cref; }
/* Watcher &operator=(Watcher w) {
this->cref = w.cref;
this->blocker = w.blocker;
return *this;
}
*/
};
struct WatcherDeleted
{
const ClauseAllocator& ca;
WatcherDeleted(const ClauseAllocator& _ca) : ca(_ca) {}
bool operator()(const Watcher& w) const { return ca[w.cref].mark() == 1; }
};
struct VarOrderLt {
const vec<double>& activity;
bool operator () (Var x, Var y) const { return activity[x] > activity[y]; }
VarOrderLt(const vec<double>& act) : activity(act) { }
};
// Solver state:
//
int lastIndexRed;
bool ok; // If FALSE, the constraints are already unsatisfiable. No part of the solver state may be used!
double cla_inc; // Amount to bump next clause with.
vec<double> activity; // A heuristic measurement of the activity of a variable.
double var_inc; // Amount to bump next variable with.
OccLists<Lit, vec<Watcher>, WatcherDeleted>
watches; // 'watches[lit]' is a list of constraints watching 'lit' (will go there if literal becomes true).
OccLists<Lit, vec<Watcher>, WatcherDeleted>
watchesBin; // 'watches[lit]' is a list of constraints watching 'lit' (will go there if literal becomes true).
OccLists<Lit, vec<Watcher>, WatcherDeleted>
unaryWatches; // Unary watch scheme (clauses are seen when they become empty
vec<CRef> clauses; // List of problem clauses.
vec<CRef> learnts; // List of learnt clauses.
vec<CRef> permanentLearnts; // The list of learnts clauses kept permanently
vec<CRef> unaryWatchedClauses; // List of imported clauses (after the purgatory) // TODO put inside ParallelSolver
vec<lbool> assigns; // The current assignments.
vec<char> polarity; // The preferred polarity of each variable.
vec<char> forceUNSAT;
void bumpForceUNSAT(Lit q); // Handles the forces
vec<char> decision; // Declares if a variable is eligible for selection in the decision heuristic.
vec<Lit> trail; // Assignment stack; stores all assigments made in the order they were made.
vec<int> nbpos;
vec<int> trail_lim; // Separator indices for different decision levels in 'trail'.
vec<VarData> vardata; // Stores reason and level for each variable.
int qhead; // Head of queue (as index into the trail -- no more explicit propagation queue in MiniSat).
int simpDB_assigns; // Number of top-level assignments since last execution of 'simplify()'.
int64_t simpDB_props; // Remaining number of propagations that must be made before next execution of 'simplify()'.
vec<Lit> assumptions; // Current set of assumptions provided to solve by the user.
Heap<VarOrderLt> order_heap; // A priority queue of variables ordered with respect to the variable activity.
double progress_estimate;// Set by 'search()'.
bool remove_satisfied; // Indicates whether possibly inefficient linear scan for satisfied clauses should be performed in 'simplify'.
vec<unsigned int> permDiff; // permDiff[var] contains the current conflict number... Used to count the number of LBD
// UPDATEVARACTIVITY trick (see competition'09 companion paper)
vec<Lit> lastDecisionLevel;
ClauseAllocator ca;
int nbclausesbeforereduce; // To know when it is time to reduce clause database
// Used for restart strategies
bqueue<unsigned int> trailQueue,lbdQueue; // Bounded queues for restarts.
float sumLBD; // used to compute the global average of LBD. Restarts...
int sumAssumptions;
CRef lastLearntClause;
// Temporaries (to reduce allocation overhead). Each variable is prefixed by the method in which it is
// used, exept 'seen' wich is used in several places.
//
vec<char> seen;
vec<Lit> analyze_stack;
vec<Lit> analyze_toclear;
vec<Lit> add_tmp;
unsigned int MYFLAG;
// Initial reduceDB strategy
double max_learnts;
double learntsize_adjust_confl;
int learntsize_adjust_cnt;
// Resource contraints:
//
int64_t conflict_budget; // -1 means no budget.
int64_t propagation_budget; // -1 means no budget.
bool asynch_interrupt;
// Variables added for incremental mode
int incremental; // Use incremental SAT Solver
int nbVarsInitialFormula; // nb VAR in formula without assumptions (incremental SAT)
double totalTime4Sat,totalTime4Unsat;
int nbSatCalls,nbUnsatCalls;
vec<int> assumptionPositions,initialPositions;
// Main internal methods:
//
void insertVarOrder (Var x); // Insert a variable in the decision order priority queue.
Lit pickBranchLit (); // Return the next decision variable.
void newDecisionLevel (); // Begins a new decision level.
void uncheckedEnqueue (Lit p, CRef from = CRef_Undef); // Enqueue a literal. Assumes value of literal is undefined.
bool enqueue (Lit p, CRef from = CRef_Undef); // Test if fact 'p' contradicts current state, enqueue otherwise.
CRef propagate (); // Perform unit propagation. Returns possibly conflicting clause.
CRef propagateUnaryWatches(Lit p); // Perform propagation on unary watches of p, can find only conflicts
void cancelUntil (int level); // Backtrack until a certain level.
void analyze (CRef confl, vec<Lit>& out_learnt, vec<Lit> & selectors, int& out_btlevel,unsigned int &nblevels,unsigned int &szWithoutSelectors); // (bt = backtrack)
void analyzeFinal (Lit p, vec<Lit>& out_conflict); // COULD THIS BE IMPLEMENTED BY THE ORDINARIY "analyze" BY SOME REASONABLE GENERALIZATION?
bool litRedundant (Lit p, uint32_t abstract_levels); // (helper method for 'analyze()')
lbool search (int nof_conflicts); // Search for a given number of conflicts.
virtual lbool solve_ (bool do_simp = true, bool turn_off_simp = false); // Main solve method (assumptions given in 'assumptions').
virtual void reduceDB (); // Reduce the set of learnt clauses.
void removeSatisfied (vec<CRef>& cs); // Shrink 'cs' to contain only non-satisfied clauses.
void rebuildOrderHeap ();
void adaptSolver(); // Adapt solver strategies
// Maintaining Variable/Clause activity:
//
void varDecayActivity (); // Decay all variables with the specified factor. Implemented by increasing the 'bump' value instead.
void varBumpActivity (Var v, double inc); // Increase a variable with the current 'bump' value.
void varBumpActivity (Var v); // Increase a variable with the current 'bump' value.
void claDecayActivity (); // Decay all clauses with the specified factor. Implemented by increasing the 'bump' value instead.
void claBumpActivity (Clause& c); // Increase a clause with the current 'bump' value.
// Operations on clauses:
//
void attachClause (CRef cr); // Attach a clause to watcher lists.
void detachClause (CRef cr, bool strict = false); // Detach a clause to watcher lists.
void detachClausePurgatory(CRef cr, bool strict = false);
void attachClausePurgatory(CRef cr);
void removeClause (CRef cr, bool inPurgatory = false); // Detach and free a clause.
bool locked (const Clause& c) const; // Returns TRUE if a clause is a reason for some implication in the current state.
bool satisfied (const Clause& c) const; // Returns TRUE if a clause is satisfied in the current state.
template <typename T> unsigned int computeLBD(const T & lits,int end=-1);
void minimisationWithBinaryResolution(vec<Lit> &out_learnt);
virtual void relocAll (ClauseAllocator& to);
// Misc:
//
int decisionLevel () const; // Gives the current decisionlevel.
uint32_t abstractLevel (Var x) const; // Used to represent an abstraction of sets of decision levels.
CRef reason (Var x) const;
int level (Var x) const;
double progressEstimate () const; // DELETE THIS ?? IT'S NOT VERY USEFUL ...
bool withinBudget () const;
inline bool isSelector(Var v) {return (incremental && v>nbVarsInitialFormula);}
// Static helpers:
//
// Returns a random float 0 <= x < 1. Seed must never be 0.
static inline double drand(double& seed) {
seed *= 1389796;
int q = (int)(seed / 2147483647);
seed -= (double)q * 2147483647;
return seed / 2147483647; }
// Returns a random integer 0 <= x < size. Seed must never be 0.
static inline int irand(double& seed, int size) {
return (int)(drand(seed) * size); }
};
//=================================================================================================
// Implementation of inline methods:
inline CRef Solver::reason(Var x) const { return vardata[x].reason; }
inline int Solver::level (Var x) const { return vardata[x].level; }
inline void Solver::insertVarOrder(Var x) {
if (!order_heap.inHeap(x) && decision[x]) order_heap.insert(x); }
inline void Solver::varDecayActivity() { var_inc *= (1 / var_decay); }
inline void Solver::varBumpActivity(Var v) { varBumpActivity(v, var_inc); }
inline void Solver::varBumpActivity(Var v, double inc) {
if ( (activity[v] += inc) > 1e100 ) {
// Rescale:
for (int i = 0; i < nVars(); i++)
activity[i] *= 1e-100;
var_inc *= 1e-100; }
// Update order_heap with respect to new activity:
if (order_heap.inHeap(v))
order_heap.decrease(v); }
inline void Solver::claDecayActivity() { cla_inc *= (1 / clause_decay); }
inline void Solver::claBumpActivity (Clause& c) {
if ( (c.activity() += cla_inc) > 1e20 ) {
// Rescale:
for (int i = 0; i < learnts.size(); i++)
ca[learnts[i]].activity() *= 1e-20;
cla_inc *= 1e-20; } }
inline void Solver::checkGarbage(void){ return checkGarbage(garbage_frac); }
inline void Solver::checkGarbage(double gf){
if (ca.wasted() > ca.size() * gf)
garbageCollect(); }
// NOTE: enqueue does not set the ok flag! (only public methods do)
inline bool Solver::enqueue (Lit p, CRef from) { return value(p) != l_Undef ? value(p) != l_False : (uncheckedEnqueue(p, from), true); }
inline bool Solver::addClause (const vec<Lit>& ps) { ps.copyTo(add_tmp); return addClause_(add_tmp); }
inline bool Solver::addEmptyClause () { add_tmp.clear(); return addClause_(add_tmp); }
inline bool Solver::addClause (Lit p) { add_tmp.clear(); add_tmp.push(p); return addClause_(add_tmp); }
inline bool Solver::addClause (Lit p, Lit q) { add_tmp.clear(); add_tmp.push(p); add_tmp.push(q); return addClause_(add_tmp); }
inline bool Solver::addClause (Lit p, Lit q, Lit r) { add_tmp.clear(); add_tmp.push(p); add_tmp.push(q); add_tmp.push(r); return addClause_(add_tmp); }
inline bool Solver::locked (const Clause& c) const {
if(c.size()>2)
return value(c[0]) == l_True && reason(var(c[0])) != CRef_Undef && ca.lea(reason(var(c[0]))) == &c;
return
(value(c[0]) == l_True && reason(var(c[0])) != CRef_Undef && ca.lea(reason(var(c[0]))) == &c)
||
(value(c[1]) == l_True && reason(var(c[1])) != CRef_Undef && ca.lea(reason(var(c[1]))) == &c);
}
inline void Solver::newDecisionLevel() { trail_lim.push(trail.size()); }
inline int Solver::decisionLevel () const { return trail_lim.size(); }
inline uint32_t Solver::abstractLevel (Var x) const { return 1 << (level(x) & 31); }
inline lbool Solver::value (Var x) const { return assigns[x]; }
inline lbool Solver::value (Lit p) const { return assigns[var(p)] ^ sign(p); }
inline lbool Solver::modelValue (Var x) const { return model[x]; }
inline lbool Solver::modelValue (Lit p) const { return model[var(p)] ^ sign(p); }
inline int Solver::nAssigns () const { return trail.size(); }
inline int Solver::nClauses () const { return clauses.size(); }
inline int Solver::nLearnts () const { return learnts.size(); }
inline int Solver::nVars () const { return vardata.size(); }
inline int Solver::nFreeVars () {
int a = stats[dec_vars];
return (int)(a) - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]); }
inline void Solver::setPolarity (Var v, bool b) { polarity[v] = b; }
inline void Solver::setDecisionVar(Var v, bool b)
{
if ( b && !decision[v]) stats[dec_vars]++;
else if (!b && decision[v]) stats[dec_vars]--;
decision[v] = b;
insertVarOrder(v);
}
inline void Solver::setConfBudget(int64_t x){ conflict_budget = conflicts + x; }
inline void Solver::setPropBudget(int64_t x){ propagation_budget = propagations + x; }
inline void Solver::interrupt(){ asynch_interrupt = true; }
inline void Solver::clearInterrupt(){ asynch_interrupt = false; }
inline void Solver::budgetOff(){ conflict_budget = propagation_budget = -1; }
inline bool Solver::withinBudget() const {
return !asynch_interrupt &&
(conflict_budget < 0 || conflicts < (uint64_t)conflict_budget) &&
(propagation_budget < 0 || propagations < (uint64_t)propagation_budget); }
// FIXME: after the introduction of asynchronous interrruptions the solve-versions that return a
// pure bool do not give a safe interface. Either interrupts must be possible to turn off here, or
// all calls to solve must return an 'lbool'. I'm not yet sure which I prefer.
inline bool Solver::solve () { budgetOff(); assumptions.clear(); return solve_() == l_True; }
inline bool Solver::solve (Lit p) { budgetOff(); assumptions.clear(); assumptions.push(p); return solve_() == l_True; }
inline bool Solver::solve (Lit p, Lit q) { budgetOff(); assumptions.clear(); assumptions.push(p); assumptions.push(q); return solve_() == l_True; }
inline bool Solver::solve (Lit p, Lit q, Lit r) { budgetOff(); assumptions.clear(); assumptions.push(p); assumptions.push(q); assumptions.push(r); return solve_() == l_True; }
inline bool Solver::solve (const vec<Lit>& assumps){ budgetOff(); assumps.copyTo(assumptions); return solve_() == l_True; }
inline lbool Solver::solveLimited (const vec<Lit>& assumps){ assumps.copyTo(assumptions); return solve_(); }
inline bool Solver::okay () const { return ok; }
inline void Solver::toDimacs (const char* file){ vec<Lit> as; toDimacs(file, as); }
inline void Solver::toDimacs (const char* file, Lit p){ vec<Lit> as; as.push(p); toDimacs(file, as); }
inline void Solver::toDimacs (const char* file, Lit p, Lit q){ vec<Lit> as; as.push(p); as.push(q); toDimacs(file, as); }
inline void Solver::toDimacs (const char* file, Lit p, Lit q, Lit r){ vec<Lit> as; as.push(p); as.push(q); as.push(r); toDimacs(file, as); }
//=================================================================================================
// Debug etc:
inline void Solver::printLit(Lit l)
{
printf("%s%d:%c", sign(l) ? "-" : "", var(l)+1, value(l) == l_True ? '1' : (value(l) == l_False ? '0' : 'X'));
}
inline void Solver::printClause(CRef cr)
{
Clause &c = ca[cr];
for (int i = 0; i < c.size(); i++){
printLit(c[i]);
printf(" ");
}
}
inline void Solver::printInitialClause(CRef cr)
{
Clause &c = ca[cr];
for (int i = 0; i < c.size(); i++){
if(!isSelector(var(c[i]))) {
printLit(c[i]);
printf(" ");
}
}
}
//=================================================================================================
struct reduceDBAct_lt {
ClauseAllocator& ca;
reduceDBAct_lt(ClauseAllocator& ca_) : ca(ca_) {
}
bool operator()(CRef x, CRef y) {
// Main criteria... Like in MiniSat we keep all binary clauses
if (ca[x].size() > 2 && ca[y].size() == 2) return 1;
if (ca[y].size() > 2 && ca[x].size() == 2) return 0;
if (ca[x].size() == 2 && ca[y].size() == 2) return 0;
return ca[x].activity() < ca[y].activity();
}
};
struct reduceDB_lt {
ClauseAllocator& ca;
reduceDB_lt(ClauseAllocator& ca_) : ca(ca_) {
}
bool operator()(CRef x, CRef y) {
// Main criteria... Like in MiniSat we keep all binary clauses
if (ca[x].size() > 2 && ca[y].size() == 2) return 1;
if (ca[y].size() > 2 && ca[x].size() == 2) return 0;
if (ca[x].size() == 2 && ca[y].size() == 2) return 0;
// Second one based on literal block distance
if (ca[x].lbd() > ca[y].lbd()) return 1;
if (ca[x].lbd() < ca[y].lbd()) return 0;
// Finally we can use old activity or size, we choose the last one
return ca[x].activity() < ca[y].activity();
//return x->size() < y->size();
//return ca[x].size() > 2 && (ca[y].size() == 2 || ca[x].activity() < ca[y].activity()); }
}
};
}
#endif
