public static bool Satisfiable(LPSConstraint ct, Vector<double> image_plus_eps)
{
// Native inner product more efficient
double lhs = image_plus_eps * ct.Term.GetCoefficients(); // ct.Term.GetCoefficients().SubVector(0, image.Count);
double rhs = 0.0;
bool sat = false;
rhs = -ct.Term.Intercept;
switch (ct.Inequality)
{
case InequalityType.EQ:
sat = (lhs == rhs);
break;
case InequalityType.GE:
sat = (lhs >= rhs);
break;
case InequalityType.GT:
sat = (lhs > rhs);
break;
case InequalityType.LE:
sat = (lhs <= rhs);
break;
case InequalityType.LT:
sat = (lhs < rhs);
break;
}
return sat;
}
public void AddConstraint(LPSConstraint ct)
{
int ctid = ct_cnt;
solver_.AddRow("constraint" + ct_cnt, out ctid);
Vector <double> coefficients = ct.Term.GetCoefficients();
int totalvars = LPSTerm.TotalVarCount();
for (int j = 0; j < totalvars; j++)
{
// Due to the way MSF works, if we are adding a 0 coefficient
// this amounts to actually removing it. However, the coefficient
// is not there to start with, hence let's not add it, at all!
if (coefficients[j] != 0)
{
solver_.SetCoefficient(ctid, vars_[j], coefficients[j]);
}
}
switch (ct.Inequality)
{
case InequalityType.LT:
solver_.SetUpperBound(ctid, -ct.Term.Intercept); // - RobustnessOptions.StrictInequalityLambda * Math.Abs(ct.Term.Intercept));
break;
case InequalityType.LE:
solver_.SetUpperBound(ctid, -ct.Term.Intercept);
break;
case InequalityType.GT:
solver_.SetLowerBound(ctid, -ct.Term.Intercept); // + RobustnessOptions.StrictInequalityLambda * Math.Abs(ct.Term.Intercept));
break;
case InequalityType.GE:
solver_.SetLowerBound(ctid, -ct.Term.Intercept);
break;
case InequalityType.EQ:
// solver_.SetValue(ctid, -ct.Term.Intercept); WRONG
solver_.SetBounds(ctid, -ct.Term.Intercept, -ct.Term.Intercept);
break;
default:
break;
}
ct_cnt++;
}
