public void JointDistributionConstructorTest2()
{
int[] symbols = { 3, 5, 2 };
JointDistribution target = new JointDistribution(symbols);
double[] p = target.Frequencies;
Assert.AreEqual(3 * 5 * 2, p.Length);
for (int i = 0; i < p.Length; i++)
p[i] = i;
double actual;
actual = target.ProbabilityMassFunction(new int[] { 0, 0, 0 });
Assert.AreEqual(0, actual);
actual = target.ProbabilityMassFunction(new int[] { 0, 0, 1 });
Assert.AreEqual(1, actual);
actual = target.ProbabilityMassFunction(new int[] { 0, 1, 0 });
Assert.AreEqual(2, actual);
actual = target.ProbabilityMassFunction(new int[] { 0, 1, 1 });
Assert.AreEqual(3, actual);
actual = target.ProbabilityMassFunction(new int[] { 0, 2, 0 });
Assert.AreEqual(4, actual);
actual = target.ProbabilityMassFunction(new int[] { 0, 2, 1 });
Assert.AreEqual(5, actual);
actual = target.ProbabilityMassFunction(new int[] { 2, 4, 1 });
Assert.AreEqual(29, actual);
}
/// <summary>
/// Estimates a new <see cref="JointDistribution"/> from a given set of observations.
/// </summary>
///
/// <example>
/// Please see <see cref="JointDistribution"/>.
/// </example>
///
public static JointDistribution Estimate(int[][] values)
{
var joint = new JointDistribution(values.DistinctCount());
joint.Fit(values);
return(joint);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
public override object Clone()
{
JointDistribution d = new JointDistribution(base.Dimension);
d.positions = this.positions.Copy();
d.probabilities = this.probabilities.Copy();
d.symbols = this.symbols.Copy();
d.start = this.start.Copy();
return(d);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
public override object Clone()
{
JointDistribution d = new JointDistribution(base.Dimension);
d.positions = (int[])this.positions.Clone();
d.probabilities = (double[])this.probabilities.Clone();
d.symbols = (int[])this.symbols.Clone();
return(d);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
public override object Clone()
{
JointDistribution d = new JointDistribution(base.Dimension);
d.positions = (int[])this.positions.Clone();
d.probabilities = (double[])this.probabilities.Clone();
d.symbols = (int[])this.symbols.Clone();
return d;
}
public void MeanTest3()
{
var target = new JointDistribution(new[] { 2 }, new [] { 0.5, 0.5 });
double expected = (2.0 + 3.0) / 2.0;
double actual = target.Mean[0];
Assert.AreEqual(expected, actual);
}
public void MeanTest2()
{
var target = new JointDistribution(new [] { 42 }, new[] { 0.1, 0.4, 0.5 });
double expected = 42 * 0.1 + 43 * 0.4 + 44 * 0.5;
double actual = target.Mean[0];
Assert.AreEqual(expected, actual);
}
public void DistributionFunctionTest()
{
var target = new JointDistribution(new[] { 0.1, 0.4, 0.5 });
double actual;
actual = target.DistributionFunction(new[] { 0 });
Assert.AreEqual(0.1, actual, 1e-6);
actual = target.DistributionFunction(new[] { 1 });
Assert.AreEqual(0.5, actual, 1e-6);
actual = target.DistributionFunction(new[] { 2 });
Assert.AreEqual(1.0, actual, 1e-6);
actual = target.DistributionFunction(new[] { 3 });
Assert.AreEqual(1.0, actual, 1e-6);
}
public void FitTest_vector_inputs()
{
double[] expected = { 0.50, 0.00, 0.25, 0.25 };
JointDistribution target;
double[] values = { 0.00, 2.00, 3.00 };
double[] weights = { 0.50, 0.25, 0.25 };
target = new JointDistribution(new[] { 4 });
target.Fit(Jagged.ColumnVector(values), weights);
double[] actual = target.Frequencies;
Assert.IsTrue(Matrix.IsEqual(expected, actual));
}
public void FitTest4()
{
double[] expected = { 0.50, 0.00, 0.25, 0.25 };
JointDistribution target;
double[] values = { 0.00, 2.00, 3.00 };
double[] weights = { 0.50, 0.25, 0.25 };
target = new JointDistribution(new[] { -1 }, new[] { 4 });
target.Fit(Jagged.ColumnVector(values).Subtract(1), weights);
double[] actual = target.Frequencies;
Assert.IsTrue(Matrix.IsEqual(expected, actual));
// --
double[] values2 = { 0.00, 0.00, 2.00, 3.00 };
double[] weights2 = { 0.25, 0.25, 0.25, 0.25 };
target = new JointDistribution(new[] { -1 }, new[] { 4 });
target.Fit(Jagged.ColumnVector(values2).Subtract(1), weights2);
double[] actual2 = target.Frequencies;
Assert.IsTrue(Matrix.IsEqual(expected, actual2));
}
public void FitTest2()
{
int[] symbols = { 3, 5 };
JointDistribution target = new JointDistribution(symbols);
double[][] observations =
{
new double[] { 0, 0 },
new double[] { 1, 1 },
new double[] { 2, 1 },
};
double[] weights = { 2, 1, 1 };
target.Fit(observations, weights);
double[] p = target.Frequencies;
double actual;
actual = target.ProbabilityMassFunction(new[] { 0, 0 });
Assert.AreEqual(0.5, actual);
actual = target.ProbabilityMassFunction(new[] { 1, 1 });
Assert.AreEqual(0.25, actual);
actual = target.ProbabilityMassFunction(new[] { 2, 1 });
Assert.AreEqual(0.25, actual);
}