public void MahalanobisTest()
{
double[] x = { 1, 0 };
double[,] y =
{
{ 1, 0 },
{ 0, 8 },
{ 0, 5 }
};
// Computing the mean of y
double[] meanY = Tools.Mean(y);
// Computing the covariance matrix of y
double[,] covY = Tools.Covariance(y, meanY);
// Inverting the covariance matrix
double[,] precision = covY.Inverse();
// Run actual test
double expected = 1.33333;
double actual = Distance.SquareMahalanobis(x, meanY, precision);
Assert.AreEqual(expected, actual, 0.0001);
}
public void MeanTest3()
{
double[] values = { -5, 0.2, 2 };
double expected = -0.93333333333333324;
double actual = Tools.Mean(values);
Assert.AreEqual(expected, actual);
}
public void MeanTest()
{
double[,] matrix =
{
{ 2, -1.0, 5 },
{ 7, 0.5, 9 },
};
double[] rowMean = Tools.Mean(matrix, 0);
Assert.IsTrue(rowMean.IsEqual(4.5000, -0.2500, 7.0000));
double[] colMean = Tools.Mean(matrix, 1);
Assert.IsTrue(colMean.IsEqual(2, 5.5));
}
public void MeanTest4()
{
double[,] matrix =
{
{ 2, -1.0, 5 },
{ 7, 0.5, 9 },
};
double[] sums = Matrix.Sum(matrix);
Assert.IsTrue(sums.IsEqual(9.0, -0.5, 14.0));
double[] expected = { 4.5000, -0.2500, 7.0000 };
double[] actual = Tools.Mean(matrix, sums);
Assert.IsTrue(expected.IsEqual(actual));
}
public void StandardDeviationTest3()
{
double[,] matrix =
{
{ 2, -1.0, 5 },
{ 7, 0.5, 9 },
};
double[] means = Tools.Mean(matrix);
Assert.IsTrue(means.IsEqual(4.5000, -0.2500, 7.0000));
double[] stdev = Tools.StandardDeviation(matrix, means);
Assert.IsTrue(stdev.IsEqual(3.5355339059327378, 1.0606601717798212, 2.8284271247461903));
double[] stdev2 = Tools.StandardDeviation(matrix);
Assert.IsTrue(stdev2.IsEqual(stdev));
}
public void CenteringTest()
{
double[,] C2 = Matrix.Centering(2);
Assert.IsTrue(Matrix.IsEqual(C2, new double[, ] {
{ 0.5, -0.5 },
{ -0.5, 0.5 }
}));
double[,] X =
{
{ 1, 5, 2, 0 },
{ 6, 2, 3, 100 },
{ 2, 5, 8, 2 },
};
double[,] CX = Matrix.Centering(3).Multiply(X); // Remove means from rows
double[,] XC = X.Multiply(Matrix.Centering(4)); // Remove means from columns
double[] colMean = Tools.Mean(X, 1);
double[] rowMean = Tools.Mean(X, 0);
Assert.IsTrue(rowMean.IsEqual(new double[] { 3.0, 4.0, 4.3333, 34.0 }, 0.001));
Assert.IsTrue(colMean.IsEqual(new double[] { 2.0, 27.75, 4.25 }, 0.001));
double[,] Xr = X.Subtract(rowMean, 0); // Remove means from rows
double[,] Xc = X.Subtract(colMean, 1); // Remove means from columns
Assert.IsTrue(Matrix.IsEqual(XC, Xc));
Assert.IsTrue(Matrix.IsEqual(CX, Xr, 0.00001));
double[,] S1 = XC.Multiply(X.Transpose());
double[,] S2 = Xc.Multiply(Xc.Transpose());
double[,] S3 = Tools.Scatter(X, colMean, 1);
Assert.IsTrue(Matrix.IsEqual(S1, S2));
Assert.IsTrue(Matrix.IsEqual(S2, S3));
}
public void MedianTest()
{
double[,] matrix =
{
{ 2, -1.0, 5 },
{ 7, 1.7, 9 },
{ -4, 2.5, 6 },
{ 0.2, 0.5, -2 },
};
double[] mean = Tools.Mean(matrix);
Assert.IsTrue(mean.IsEqual(1.3000, 0.9250, 4.5000));
double[] median = Tools.Median(matrix);
Assert.IsTrue(median.IsEqual(1.1000, 1.1000, 5.5000));
matrix = matrix.Transpose();
mean = Tools.Mean(matrix);
Assert.IsTrue(mean.IsEqual(2.0000, 5.8999999999999995, 1.5000, -0.43333333333333335));
median = Tools.Median(matrix);
Assert.IsTrue(median.IsEqual(2.0000, 7.0000, 2.5000, 0.2000));
}
