public void JaggedSingularValueDecompositionConstructorTest5()
{
// Test using SVD assumption auto-correction feature
// without computing the left singular vectors.
var value = new double[][]
{
new double[] { 1, 2 },
new double[] { 3, 4 },
new double[] { 5, 6 },
new double[] { 7, 8 }
}.Transpose(); // value is 2x4, having less rows than columns.
var target = new JaggedSingularValueDecomposition(value, false, true, true);
// Checking values
double[][] U =
{
new double[] { 0.0, 0.0 },
new double[] { 0.0, 0.0 },
};
// U should not have been computed
Assert.IsTrue(Matrix.IsEqual(target.LeftSingularVectors, U));
double[][] V = // economy svd
{
new double[] { 0.152483233310201, 0.822647472225661, },
new double[] { 0.349918371807964, 0.421375287684580, },
new double[] { 0.547353510305727, 0.0201031031435023, },
new double[] { 0.744788648803490, -0.381169081397574, },
};
// V can be different, but for the economy SVD it is often equal
Assert.IsTrue(Matrix.IsEqual(target.RightSingularVectors, V, 0.0001));
double[][] S =
{
new double[] { 14.2690954992615, 0.000000000000000 },
new double[] { 0.0000000000000, 0.626828232417543 },
};
// The diagonal values should be equal
Assert.IsTrue(Matrix.IsEqual(target.Diagonal, Matrix.Diagonal(S), 0.001));
}