internal void Defuzzify_WithTwoTriangles_ReturnsExpectedResult()
{
// Arrange
var fuzzySet1 = new FuzzySet("left", TriangularFunction.Create(1, 2, 3));
var fuzzySet2 = new FuzzySet("right", TriangularFunction.Create(3, 4, 5));
var fuzzyOutput = new List <FuzzyOutput>
{
new FuzzyOutput(
Label.Create("Balance"),
fuzzySet1,
UnitInterval.One()),
new FuzzyOutput(
Label.Create("Balance"),
fuzzySet2,
UnitInterval.One())
};
var centroidDefuzzifier = new CentroidDefuzzifier();
// Act
var result = centroidDefuzzifier.Defuzzify(fuzzyOutput);
// Assert
Assert.Equal("Balance", result.Subject.Value);
Assert.Equal(3, result.Value);
}
internal void IsNormal_WhenSetNotNormal_ReturnsFalse()
{
// Arrange
var function = TriangularFunction.Create(2, 3, 4, 0, 0.9);
var fuzzySet = new FuzzySet("some_fuzzy_state", function);
// Act
var result = fuzzySet.IsNormal;
// Assert
Assert.False(result);
}
internal void Complement_VariousInputs_ReturnsExpectedResult(double input, double expected)
{
// Arrange
var function = TriangularFunction.Create(2, 3, 4);
var fuzzySet = new FuzzySet("some_fuzzy_state", function);
// Act
var result = fuzzySet.Complement(input);
// Assert
Assert.Equal(UnitInterval.Create(expected), result);
}
internal void GetMembership_VariousInputs_ReturnsExpectedResult(double input, double expected)
{
// Arrange
var function = TriangularFunction.Create(2, 3, 4);
var fuzzySet = new FuzzySet("some_fuzzy_state", function);
// Act
var result = fuzzySet.GetMembership(input);
// Assert
Assert.Equal(UnitInterval.Create(expected), result);
Assert.Equal("some_fuzzy_state", fuzzySet.State.Value);
}
internal void Intersection_VariousInputs_ReturnsExpectedResult(double input, double expected)
{
// Arrange
var function1 = TriangularFunction.Create(1, 3, 5);
var function2 = TriangularFunction.Create(2, 4, 6, 0, 0.75);
var fuzzySet1 = new FuzzySet("some_fuzzy_state1", function1);
var fuzzySet2 = new FuzzySet("some_fuzzy_state2", function2);
// Act
var result = fuzzySet1.Intersection(fuzzySet2, input);
// Assert
Assert.Equal(UnitInterval.Create(expected), result);
}
/// <summary>
/// Returns a <see cref="LinguisticVariable"/> representing fan speed.
/// </summary>
/// <returns>
/// The <see cref="LinguisticVariable"/>.
/// </returns>
public static LinguisticVariable PumpSpeed()
{
return(new LinguisticVariable(
InputVariable.PumpSpeed,
new List <FuzzySet>
{
new FuzzySet(TestKit.PumpSpeed.Off, SingletonFunction.Create(0)),
new FuzzySet(TestKit.PumpSpeed.VeryLow, TrapezoidalFunction.CreateWithLeftEdge(1, 200)),
new FuzzySet(TestKit.PumpSpeed.Low, TriangularFunction.Create(0, 500, 1000)),
new FuzzySet(TestKit.PumpSpeed.Moderate, TriangularFunction.Create(500, 1000, 2000)),
new FuzzySet(TestKit.PumpSpeed.High, TriangularFunction.Create(3000, 3500, 4000)),
new FuzzySet(TestKit.PumpSpeed.VeryHigh, TrapezoidalFunction.CreateWithRightEdge(3500, 4999)),
new FuzzySet(TestKit.PumpSpeed.AtLimit, SingletonFunction.Create(5000))
}));
}
/// <summary>
/// Returns a <see cref="LinguisticVariable"/> representing water temperature.
/// </summary>
/// <returns>
/// The <see cref="LinguisticVariable"/>.
/// </returns>
public static LinguisticVariable WaterTemp()
{
return(new LinguisticVariable(
InputVariable.WaterTemp,
new List <FuzzySet>
{
new FuzzySet(TestKit.WaterTemp.Frozen, SingletonFunction.Create(0)),
new FuzzySet(TestKit.WaterTemp.Freezing, TriangularFunction.Create(0, 5, 10)),
new FuzzySet(TestKit.WaterTemp.Cold, TrapezoidalFunction.Create(5, 10, 15, 20)),
new FuzzySet(TestKit.WaterTemp.Warm, TrapezoidalFunction.Create(15, 25, 35, 40)),
new FuzzySet(TestKit.WaterTemp.Hot, TrapezoidalFunction.Create(35, 60, 80, 100)),
new FuzzySet(TestKit.WaterTemp.Boiling, TrapezoidalFunction.CreateWithRightEdge(95, 100))
},
-20,
200));
}
internal void GetMembership_VariousInputs_ReturnsExpectedResult(
double x1,
double x2,
double x3,
double input,
double expected)
{
// Arrange
var function = TriangularFunction.Create(x1, x2, x3);
// Act
var result = function.GetMembership(input);
// Assert
Assert.Equal(UnitInterval.Create(expected), result);
}
internal void Defuzzify_WithTriangle_ReturnsExpectedResult()
{
// Arrange
var fuzzySet = new FuzzySet("centre", TriangularFunction.Create(-1, 0, 1));
var fuzzyOutput = new List <FuzzyOutput>
{
new FuzzyOutput(
Label.Create("Balance"),
fuzzySet,
UnitInterval.Create(0.5))
};
var centroidDefuzzifier = new CentroidDefuzzifier();
// Act
var result = centroidDefuzzifier.Defuzzify(fuzzyOutput);
// Assert
Assert.Equal("Balance", result.Subject.Value);
Assert.Equal(0, result.Value);
}
internal void Defuzzify_WhenSubjectsUnrelated_Throws()
{
// Arrange
var fuzzySet = new FuzzySet("centre", TriangularFunction.Create(-1, 0, 1));
var fuzzyOutput = new List <FuzzyOutput>
{
new FuzzyOutput(
Label.Create("Subject1"),
fuzzySet,
UnitInterval.One()),
new FuzzyOutput(
Label.Create("Subject2"),
fuzzySet,
UnitInterval.One())
};
var centroidDefuzzifier = new CentroidDefuzzifier();
// Act
// Assert
Assert.Throws <InvalidOperationException>(() => centroidDefuzzifier.Defuzzify(fuzzyOutput));
}
internal void RunMamdaniInference(double foodInput, double serviceInput, double expected)
{
// Define the input and output linguistic variables.
var foodQuality = new LinguisticVariable(
InputVariable.FoodQuality,
new List <FuzzySet>
{
new FuzzySet(FoodQuality.Poor, TrapezoidalFunction.CreateWithLeftEdge(0, 5)),
new FuzzySet(FoodQuality.Average, TriangularFunction.Create(0, 5, 10)),
new FuzzySet(FoodQuality.Good, TrapezoidalFunction.CreateWithRightEdge(5, 10))
});
var serviceQuality = new LinguisticVariable(
InputVariable.FoodQuality,
new List <FuzzySet>
{
new FuzzySet(ServiceQuality.Poor, TrapezoidalFunction.CreateWithLeftEdge(0, 5)),
new FuzzySet(ServiceQuality.Average, TriangularFunction.Create(0, 5, 10)),
new FuzzySet(ServiceQuality.Good, TrapezoidalFunction.CreateWithRightEdge(5, 10))
});
var tipAmount = new LinguisticVariable(
OutputVariable.TipAmount,
new List <FuzzySet>
{
new FuzzySet(TipAmount.Low, TrapezoidalFunction.CreateWithLeftEdge(0, 13)),
new FuzzySet(TipAmount.Medium, TriangularFunction.Create(0, 13, 25)),
new FuzzySet(TipAmount.High, TrapezoidalFunction.CreateWithRightEdge(13, 25))
});
// Define the rules for the fuzzy inference engine.
var rule1 = new FuzzyRuleBuilder(TippingProblem.Rule1)
.If(foodQuality.Is(FoodQuality.Poor))
.Or(serviceQuality.Is(ServiceQuality.Poor))
.Then(tipAmount.Is(TipAmount.Low))
.Build();
var rule2 = new FuzzyRuleBuilder(TippingProblem.Rule2)
.If(serviceQuality.Is(ServiceQuality.Average))
.Then(tipAmount.Is(TipAmount.Medium))
.Build();
var rule3 = new FuzzyRuleBuilder(TippingProblem.Rule3)
.If(foodQuality.Is(FoodQuality.Good))
.Or(serviceQuality.Is(ServiceQuality.Good))
.Then(tipAmount.Is(TipAmount.High))
.Build();
// Construct the fuzzy inference engine.
var tnorm = TriangularNormFactory.MinimumTNorm();
var tconorm = TriangularConormFactory.MaximumTConorm();
var defuzzifier = new CentroidDefuzzifier();
var fuzzyEngine = new MamdaniInferenceEngine(tnorm, tconorm, defuzzifier);
// Add the rules to the rulebase.
fuzzyEngine.Rulebase.AddRule(rule1);
fuzzyEngine.Rulebase.AddRule(rule2);
fuzzyEngine.Rulebase.AddRule(rule3);
// Prepare database to receive inputs.
fuzzyEngine.Database.AddVariable(Label.Create(InputVariable.FoodQuality));
fuzzyEngine.Database.AddVariable(Label.Create(InputVariable.ServiceQuality));
// Generate input data.
var foodData = new DataPoint(InputVariable.FoodQuality, foodInput);
var serviceData = new DataPoint(InputVariable.ServiceQuality, serviceInput);
// Feed inference engine the data.
fuzzyEngine.Database.UpdateData(foodData);
fuzzyEngine.Database.UpdateData(serviceData);
// Compute the inference engine.
var result = fuzzyEngine.Compute();
Assert.Equal(OutputVariable.TipAmount.ToString(), result[0].Subject.Value);
Assert.Equal(expected, result[0].Value);
}
