bool MPI_Base :: MakeAssignsFromMasks( unsigned *full_mask,
unsigned *part_mask,
unsigned *mask_value,
vec< vec<Lit> > &dummy_vec )
{
// for predict with minisat2.2. convert masks to vector of Literals
unsigned variate_vars_count = 0;
full_mask_var_count = 0;
for ( unsigned i = 0; i < FULL_MASK_LEN; i++ ) {
variate_vars_count += BitCount( full_mask[i] ^ part_mask[i] );
full_mask_var_count += BitCount( full_mask[i] );
}
// determine count of assumptions and lenght of every one
int problems_count = 1 << variate_vars_count;
dummy_vec.resize( problems_count );
for( int i=0; i < dummy_vec.size(); ++i )
dummy_vec[i].resize( full_mask_var_count );
unsigned mask, range_mask_ind;
int range_mask;
unsigned index;
int cur_var_ind;
bool IsPositiveLiteral, IsAddingLiteral;
for ( int lint = 0; lint < problems_count; lint++ ) {
range_mask = 1;
range_mask_ind = 1;
index = 0;
for ( unsigned i = 0; i < FULL_MASK_LEN; i++ ) {
for ( unsigned j = 0; j < UINT_LEN; j++ ) {
mask = ( 1 << j );
cur_var_ind = i * UINT_LEN + j;
IsAddingLiteral = false;
if ( part_mask[i] & mask ) { // one common vector send by control process
IsPositiveLiteral = ( mask_value[i] & mask ) ? true : false;
IsAddingLiteral = true;
}
else if ( full_mask[i] & mask ) { // set of vectors
IsPositiveLiteral = ( lint & range_mask ) ? true : false;
range_mask = 1 << range_mask_ind;
range_mask_ind++;
IsAddingLiteral = true;
}
if ( !IsAddingLiteral ) continue;
dummy_vec[lint][index++] = IsPositiveLiteral ? mkLit( cur_var_ind ) : ~mkLit( cur_var_ind );
}
}
}
return true;
}
inline Lit mkNegLit (Atom var) { return mkLit(var, true); }
inline Lit mkPosLit (Atom var) { return mkLit(var, false); }
