public void Multiply2x3by3x2()
{
double[,] matrix1 = new double[, ]
{
{ 1, 2, 3 },
{ 4, 5, 6 }
};
double[,] matrix2 = new double[, ]
{
{ 7, 8 },
{ 9, 10 },
{ 11, 12 }
};
double[,] multiplied = MatrixMxN.MultiplyMatrix(matrix1, matrix2);
Assert.AreEqual(2, multiplied.GetLength(0));
Assert.AreEqual(2, multiplied.GetLength(1));
double[,] expected = new double[, ]
{
{ 58, 64 },
{ 139, 154 }
};
for (int i = 0; i < 2; i++)
{
for (int j = 0; j < 2; j++)
{
Assert.AreEqual(expected[i, j], Math.Round(multiplied[i, j], 5));
}
}
}
public void Multiply2x2by2x2()
{
double[,] matrix1 = new double[, ]
{
{ 1, 2 },
{ 4, 5 }
};
double[,] matrix2 = new double[, ]
{
{ 7, 8 },
{ 9, 10 }
};
double[,] multiplied = MatrixMxN.MultiplyMatrix(matrix1, matrix2);
Assert.AreEqual(2, multiplied.GetLength(0));
Assert.AreEqual(2, multiplied.GetLength(1));
double[,] expected = new double[, ]
{
{ 25, 28 },
{ 73, 82 }
};
for (int i = 0; i < 2; i++)
{
for (int j = 0; j < 2; j++)
{
Assert.AreEqual(expected[i, j], Math.Round(multiplied[i, j], 5));
}
}
}
public void MultiplySingle1x3by3x4()
{
double[] matrix1 = new double[]
{
3, 4, 2
};
double[,] matrix2 = new double[, ]
{
{ 13, 9, 7, 15 },
{ 8, 7, 4, 6 },
{ 6, 4, 0, 3 }
};
double[] multiplied = MatrixMxN.MultiplyMatrix(matrix1, matrix2);
Assert.AreEqual(4, multiplied.Length);
double[] expected = new double[]
{
83, 63, 37, 75
};
for (int i = 0; i < 4; i++)
{
Assert.AreEqual(expected[i], Math.Round(multiplied[i], 5));
}
}
public void Multiply1x3by3x4()
{
double[,] matrix1 = new double[, ]
{
{ 3, 4, 2 }
};
double[,] matrix2 = new double[, ]
{
{ 13, 9, 7, 15 },
{ 8, 7, 4, 6 },
{ 6, 4, 0, 3 }
};
double[,] multiplied = MatrixMxN.MultiplyMatrix(matrix1, matrix2);
Assert.AreEqual(1, multiplied.GetLength(0));
Assert.AreEqual(4, multiplied.GetLength(1));
double[,] expected = new double[, ]
{
{ 83, 63, 37, 75 }
};
for (int i = 0; i < 1; i++)
{
for (int j = 0; j < 4; j++)
{
Assert.AreEqual(expected[i, j], Math.Round(multiplied[i, j], 5));
}
}
}
public static double[,] CovarianceToCorrelation(double[,] covariance)
{
int dimensions = covariance.GetLength(0);
double[,] correlation = new double[dimensions, dimensions];
for (int j = 0; j < dimensions; j++)
{
for (int i = 0; i < dimensions; i++)
{
if (i != j)
{
continue;
}
correlation[i, j] = Math.Sqrt(covariance[i, j]);
}
}
double[,] inverse = MatrixMxN.Inverse(correlation);
return(MatrixMxN.MultiplyMatrix(MatrixMxN.MultiplyMatrix(inverse, covariance), inverse));
}
public override double MahalanobisDistance(double[] x)
{
if (x.Length != Dimension)
{
throw new ArgumentException("X must be the same size as distributions dimension.");
}
double[] xm = new double[Dimension];
for (int i = 0; i < Dimension; i++)
{
xm[i] = x[i] - Mean[i];
}
double[] xmTC = MatrixMxN.MultiplyMatrix(xm, Inverse);
double dp = 0;
for (int i = 0; i < Dimension; i++)
{
dp += xmTC[i] * xm[i];
}
return(Math.Sqrt(dp));
}
