public void ToArray1D()
{
Matrix33D m = new Matrix33D(1, 2, 3, 4, 5, 6, 7, 8, 9);
double[] array = m.ToArray1D(MatrixOrder.RowMajor);
for (int i = 0; i < 9; i++)
Assert.AreEqual(rowMajor[i], array[i]);
array = m.ToArray1D(MatrixOrder.ColumnMajor);
for (int i = 0; i < 9; i++)
Assert.AreEqual(columnMajor[i], array[i]);
}
public void ToArray1D()
{
Matrix33D m = new Matrix33D(1, 2, 3, 4, 5, 6, 7, 8, 9);
double[] array = m.ToArray1D(MatrixOrder.RowMajor);
for (int i = 0; i < 9; i++)
Assert.AreEqual(rowMajor[i], array[i]);
array = m.ToArray1D(MatrixOrder.ColumnMajor);
for (int i = 0; i < 9; i++)
Assert.AreEqual(columnMajor[i], array[i]);
}
public void ComputeCovarianceMatrix3F()
{
// Make a random list.
List <Vector3F> points3F = new List <Vector3F>(new[]
{
new Vector3F(-1, -2, 1),
new Vector3F(1, 0, 2),
new Vector3F(2, -1, 3),
new Vector3F(2, -1, 2),
});
Matrix33F cov3F = StatisticsHelper.ComputeCovarianceMatrix(points3F);
Assert.AreEqual(3f / 2, cov3F[0, 0]);
Assert.AreEqual(1f / 2, cov3F[0, 1]);
Assert.AreEqual(3f / 4, cov3F[0, 2]);
Assert.AreEqual(1f / 2, cov3F[1, 0]);
Assert.AreEqual(1f / 2, cov3F[1, 1]);
Assert.AreEqual(1f / 4, cov3F[1, 2]);
Assert.AreEqual(3f / 4, cov3F[2, 0]);
Assert.AreEqual(1f / 4, cov3F[2, 1]);
Assert.AreEqual(1f / 2, cov3F[2, 2]);
// Compare with Vector3D version.
List <Vector3D> points3D = new List <Vector3D>();
foreach (var point in points3F)
{
points3D.Add(point.ToVector3D());
}
Matrix33D cov3D = StatisticsHelper.ComputeCovarianceMatrix(points3D);
for (int i = 0; i < cov3F.ToArray1D(MatrixOrder.RowMajor).Length; i++)
{
var item3F = cov3F.ToArray1D(MatrixOrder.RowMajor)[i];
var item3D = cov3D.ToArray1D(MatrixOrder.RowMajor)[i];
Assert.AreEqual(item3F, item3D);
}
// Compare with VectorF version.
List <VectorF> pointsF = new List <VectorF>();
foreach (var point in points3F)
{
pointsF.Add(point.ToVectorF());
}
MatrixF covF = StatisticsHelper.ComputeCovarianceMatrix(pointsF);
for (int i = 0; i < cov3F.ToArray1D(MatrixOrder.RowMajor).Length; i++)
{
var item3F = cov3F.ToArray1D(MatrixOrder.RowMajor)[i];
var itemF = covF.ToArray1D(MatrixOrder.RowMajor)[i];
Assert.AreEqual(item3F, itemF);
}
// Compare with VectorF version.
List <VectorD> pointsD = new List <VectorD>();
foreach (var point in points3D)
{
pointsD.Add(point.ToVectorD());
}
MatrixD covD = StatisticsHelper.ComputeCovarianceMatrix(pointsD);
for (int i = 0; i < cov3F.ToArray1D(MatrixOrder.RowMajor).Length; i++)
{
var item3F = cov3F.ToArray1D(MatrixOrder.RowMajor)[i];
var itemD = covD.ToArray1D(MatrixOrder.RowMajor)[i];
Assert.AreEqual(item3F, itemD);
}
}