/// <summary>
/// Determines if the properties of the actual <see cref="TruncatedNormalDistribution"/> are the same
/// as the expected <see cref="TruncatedNormalDistribution"/>.
/// </summary>
/// <param name="expectedDistribution">The expected <see cref="TruncatedNormalDistribution"/>.</param>
/// <param name="actualDistribution">The actual <see cref="TruncatedNormalDistribution"/>.</param>
/// <exception cref="AssertionException">Thrown when the following differences are found between
/// the <paramref name="expectedDistribution"/> and <paramref name="actualDistribution"/>:
/// <list type="bullet">
/// <item>The probabilistic distribution types.</item>
/// <item>The values for the mean, the standard deviation, the lower boundary and/or the upper boundary.</item>
/// <item>The precision for the mean, the standard deviation, the lower boundary and/or the upper boundary.</item>
/// </list></exception>
public static void AreEqual(TruncatedNormalDistribution expectedDistribution, TruncatedNormalDistribution actualDistribution)
{
AreEqual((IDistribution)expectedDistribution, actualDistribution);
AreEqualValue(expectedDistribution.LowerBoundary, actualDistribution.LowerBoundary);
AreEqualValue(expectedDistribution.UpperBoundary, actualDistribution.UpperBoundary);
}
/// <summary>
/// Initializes a new instance of the <see cref="GeneralGrassCoverErosionInwardsInput"/> class.
/// </summary>
public GeneralGrassCoverErosionInwardsInput()
{
n = new RoundedDouble(numberOfDecimalPlacesN, 2.0);
CriticalOvertoppingModelFactor = 1.0;
FbFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)4.75,
StandardDeviation = (RoundedDouble)0.5,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
FnFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)2.6,
StandardDeviation = (RoundedDouble)0.35,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
OvertoppingModelFactor = 1.0;
FrunupModelFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)1,
StandardDeviation = (RoundedDouble)0.07,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
FshallowModelFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)0.92,
StandardDeviation = (RoundedDouble)0.24,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
}
public void UpperBoundary_SetNewValue_GetValueRoundedToGivenNumberOfDecimalPlaces()
{
const double value = 1.23456789;
const int numberOfDecimalPlaces = 4;
var distribution = new TruncatedNormalDistribution(numberOfDecimalPlaces);
// Call
distribution.UpperBoundary = (RoundedDouble)value;
// Assert
Assert.AreEqual(numberOfDecimalPlaces, distribution.UpperBoundary.NumberOfDecimalPlaces);
Assert.AreEqual(value, distribution.UpperBoundary, distribution.UpperBoundary.GetAccuracy());
}
public void Constructor_ExpectedValues()
{
// Setup
var fbFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)4.75,
StandardDeviation = (RoundedDouble)0.5,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
var fnFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)2.6,
StandardDeviation = (RoundedDouble)0.35,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
var fshallow = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)0.92,
StandardDeviation = (RoundedDouble)0.24,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
var frunupModelFactor = new TruncatedNormalDistribution(2)
{
Mean = (RoundedDouble)1,
StandardDeviation = (RoundedDouble)0.07,
LowerBoundary = (RoundedDouble)0.0,
UpperBoundary = (RoundedDouble)99.0
};
// Call
var inputParameters = new GeneralGrassCoverErosionInwardsInput();
// Assert
Assert.AreEqual(2, inputParameters.N.NumberOfDecimalPlaces);
Assert.AreEqual(2.0, inputParameters.N, inputParameters.N.GetAccuracy());
Assert.IsFalse(inputParameters.ApplyLengthEffectInSection);
DistributionAssert.AreEqual(fbFactor, inputParameters.FbFactor);
DistributionAssert.AreEqual(fnFactor, inputParameters.FnFactor);
DistributionAssert.AreEqual(fshallow, inputParameters.FshallowModelFactor);
DistributionAssert.AreEqual(frunupModelFactor, inputParameters.FrunupModelFactor);
Assert.AreEqual(1, inputParameters.CriticalOvertoppingModelFactor);
Assert.AreEqual(1, inputParameters.OvertoppingModelFactor);
}
public void Constructor_WithDistribution_ExpectedValues()
{
// Setup
var distribution = new TruncatedNormalDistribution(new Random(21).Next(3, RoundedDouble.MaximumNumberOfDecimalPlaces));
// Call
var properties = new TruncatedNormalDistributionProperties(distribution);
// Assert
Assert.IsInstanceOf <DistributionPropertiesBase <TruncatedNormalDistribution> >(properties);
Assert.AreSame(distribution, properties.Data);
Assert.AreEqual("Normaal (afgekapt)", properties.DistributionType);
AssertPropertiesInState(properties, true, true);
}
public void DefaultConstructor_ExpectedValues(int numberOfDecimalPlaces)
{
// Call
var distribution = new TruncatedNormalDistribution(numberOfDecimalPlaces);
// Assert
Assert.IsInstanceOf <NormalDistribution>(distribution);
Assert.AreEqual(0.0, distribution.Mean.Value);
Assert.AreEqual(numberOfDecimalPlaces, distribution.Mean.NumberOfDecimalPlaces);
Assert.AreEqual(1.0, distribution.StandardDeviation.Value);
Assert.AreEqual(numberOfDecimalPlaces, distribution.StandardDeviation.NumberOfDecimalPlaces);
Assert.AreEqual(0.0, distribution.LowerBoundary.Value);
Assert.AreEqual(numberOfDecimalPlaces, distribution.LowerBoundary.NumberOfDecimalPlaces);
Assert.AreEqual(0.0, distribution.UpperBoundary.Value);
Assert.AreEqual(numberOfDecimalPlaces, distribution.UpperBoundary.NumberOfDecimalPlaces);
}
public void Clone_Always_ReturnNewInstanceWithCopiedValues()
{
// Setup
var random = new Random(21);
var original = new TruncatedNormalDistribution(random.Next(1, 16))
{
Mean = random.NextRoundedDouble(),
StandardDeviation = random.NextRoundedDouble(),
LowerBoundary = random.NextRoundedDouble(),
UpperBoundary = random.NextRoundedDouble()
};
// Call
object clone = original.Clone();
// Assert
CoreCloneAssert.AreObjectClones(original, clone, DistributionAssert.AreEqual);
}
public void Constructor_WithParameters_ExpectedValues()
{
// Setup
var mocks = new MockRepository();
var handler = mocks.Stub <IObservablePropertyChangeHandler>();
mocks.ReplayAll();
var distribution = new TruncatedNormalDistribution(new Random(21).Next(3, RoundedDouble.MaximumNumberOfDecimalPlaces));
// Call
var properties = new TruncatedNormalDistributionProperties(DistributionReadOnlyProperties.None, distribution, handler);
// Assert
Assert.IsInstanceOf <DistributionPropertiesBase <TruncatedNormalDistribution> >(properties);
Assert.AreSame(distribution, properties.Data);
Assert.AreEqual("Normaal (afgekapt)", properties.DistributionType);
AssertPropertiesInState(properties, false, false);
mocks.VerifyAll();
}
