/// <summary>
/// Initializes a new instance of the <see cref="DenseSvd"/> class. This object will compute the
/// the singular value decomposition when the constructor is called and cache it's decomposition.
/// </summary>
/// <param name="matrix">The matrix to factor.</param>
/// <param name="computeVectors">Compute the singular U and VT vectors or not.</param>
/// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
/// <exception cref="ArgumentException">If SVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
public static DenseSvd Create(DenseMatrix matrix, bool computeVectors)
{
var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
var s = new DenseVector(nm);
var u = new DenseMatrix(matrix.RowCount);
var vt = new DenseMatrix(matrix.ColumnCount);
MathNetNumerics.ManagedLinearAlgebraProvider svder = new MathNetNumerics.ManagedLinearAlgebraProvider();
svder.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, s.Values, u.Values, vt.Values);
//LinearAlgebraControl.Provider.SingularValueDecomposition(computeVectors, ((DenseMatrix) matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, s.Values, u.Values, vt.Values);
return(new DenseSvd(s, u, vt, computeVectors));
}
/// <summary>
/// Solves a system of linear equations, <b>AX = B</b>, with A SVD factorized.
/// </summary>
/// <param name="input">The right hand side <see cref="Matrix{T}"/>, <b>B</b>.</param>
/// <param name="result">The left hand side <see cref="Matrix{T}"/>, <b>X</b>.</param>
public override void Solve(Matrix <double> input, Matrix <double> result)
{
if (!VectorsComputed)
{
throw new InvalidOperationException("Resources.SingularVectorsNotComputed");
}
// The solution X should have the same number of columns as B
if (input.ColumnCount != result.ColumnCount)
{
throw new ArgumentException("Resources.ArgumentMatrixSameColumnDimension");
}
// The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
if (U.RowCount != input.RowCount)
{
throw new ArgumentException("Resources.ArgumentMatrixSameRowDimension");
}
// The solution X row dimension is equal to the column dimension of A
if (VT.ColumnCount != result.RowCount)
{
throw new ArgumentException("Resources.ArgumentMatrixSameColumnDimension");
}
var dinput = input as DenseMatrix;
if (dinput == null)
{
throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
}
var dresult = result as DenseMatrix;
if (dresult == null)
{
throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
}
MathNetNumerics.ManagedLinearAlgebraProvider svder = new MathNetNumerics.ManagedLinearAlgebraProvider();
svder.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
//LinearAlgebraControl.Provider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector) S).Values, ((DenseMatrix) U).Values, ((DenseMatrix) VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
}
/// <summary>
/// Solves a system of linear equations, <b>Ax = b</b>, with A SVD factorized.
/// </summary>
/// <param name="input">The right hand side vector, <b>b</b>.</param>
/// <param name="result">The left hand side <see cref="Matrix{T}"/>, <b>x</b>.</param>
public override void Solve(Vector <double> input, Vector <double> result)
{
if (!VectorsComputed)
{
throw new InvalidOperationException("Resources.SingularVectorsNotComputed");
}
// Ax=b where A is an m x n matrix
// Check that b is a column vector with m entries
if (U.RowCount != input.Count)
{
throw new ArgumentException("Resources.ArgumentVectorsSameLength");
}
// Check that x is a column vector with n entries
if (VT.ColumnCount != result.Count)
{
throw Matrix.DimensionsDontMatch <ArgumentException>(VT, result);
}
var dinput = input as DenseVector;
if (dinput == null)
{
throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
}
var dresult = result as DenseVector;
if (dresult == null)
{
throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
}
MathNetNumerics.ManagedLinearAlgebraProvider svder = new MathNetNumerics.ManagedLinearAlgebraProvider();
svder.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, 1, dresult.Values);
//LinearAlgebraControl.Provider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector) S).Values, ((DenseMatrix) U).Values, ((DenseMatrix) VT).Values, dinput.Values, 1, dresult.Values);
}
