public bool Equals(double first, double second)
{
if (FuzzyCompare.InSameBoundary(first, second, _marginOfError, _ulpTolerance, _boundaryScale) &&
FuzzyCompare.AreEqual(first, second, _marginOfError, _ulpTolerance))
{
return(true);
}
return(false);
}
public bool Equals(FuzzyHashedDouble other)
{
if (_ulpTolerance == other._ulpTolerance &&
_marginOfError == other._marginOfError &&
_boundaryScale == other._boundaryScale &&
FuzzyCompare.InSameBoundary(_value, other._value, _marginOfError, _ulpTolerance, _boundaryScale) &&
FuzzyCompare.AreEqual(_value, other._value, _marginOfError, _ulpTolerance))
{
return(true);
}
return(false);
}
/**
* @brief This hash code algorithm produces a hash that complies with the guidelines set forth in the .NET documentation,
* yet is able to represent a number that is capable of fuzzy logic.
* @returns Hash for the fuzzy number.
* */
public override int GetHashCode()
{
long boundary = FuzzyCompare.Boundary(_value, _marginOfError, _ulpTolerance, _boundaryScale);
long valueAlongBoundary = FuzzyCompare.RoundToBoundary(_value, boundary);
unchecked // Overflow is fine, just wrap.
{
int hash = 17;
hash = hash * 29 + valueAlongBoundary.GetHashCode();
hash = hash * 29 + _ulpTolerance.GetHashCode();
hash = hash * 29 + _marginOfError.GetHashCode();
hash = hash * 29 + _boundaryScale.GetHashCode();
return(hash);
}
}
public bool Equals(double first, double second)
{
return(FuzzyCompare.AreEqual(first, second, _marginOfError, _ulpTolerance));
}
public bool Equals(FuzzySingle other)
{
return(FuzzyCompare.AreEqual(_value, other._value, _marginOfError, _ulpTolerance));
}