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//Copyright � 2009 Jose Antonio De Santiago-Castillo
//E-mail:JAntonioDeSantiago@gmail.com
//Web: www.DotNumerics.com
//
#endregion
using System;
using System.Collections.Generic;
using System.Text;
using System.ComponentModel;
using DotNumerics.LinearAlgebra.CSLapack;
namespace DotNumerics.LinearAlgebra
{
/// <summary>
/// Computes the singular value decomposition (SVD) of a real
/// M-by-N matrix A.
/// </summary>
/// <remarks>
/// The SVD is written
///
/// A = U * S * transpose(V)
///
/// where S is an M-by-N matrix which is zero except for its
/// min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and
/// V is an N-by-N orthogonal matrix. The diagonal elements of S
/// are the singular values of A; they are real and non-negative, and
/// are returned in descending order. The first min(m,n) columns of
/// U and V are the left and right singular vectors of A.
///
/// Note that the routine returns V**T, not V.
/// </remarks>
public sealed class SingularValueDecomposition
{
#region Fields
DGESVD _dgesvd;
#endregion
/// <summary>
/// Initializes a new instance of the SingularValues class.
/// </summary>
public SingularValueDecomposition()
{
//MeDGESVD = new DGESVD();
}
#region Public Metods
/// <summary>
///Computes the singular value decomposition (SVD) of a real
/// M-by-N matrix A.
/// The SVD is written
/// A = U * S * transpose(V)
/// </summary>
/// <param name="A">The A matrix.</param>
/// <param name="S">The diagonal elements of S are the singular values of A.</param>
public void ComputeSVD(Matrix A, out Matrix S)
{
Vector singularValues;
S = new Matrix(A.RowCount, A.ColumnCount);// A is MxN, S is MxN
this.ComputeSVD(A, out singularValues);
for (int i = 0; i < singularValues.Length; i++)
{
S[i, i] = singularValues[i];
}
}
/// <summary>
///Computes the singular value decomposition (SVD) of a real
/// M-by-N matrix A.
/// The SVD is written
/// A = U * S * transpose(V)
/// </summary>
/// <param name="A">The A matrix.</param>
/// <param name="S">A vector of singular values.</param>
public void ComputeSVD(Matrix A, out Vector S)
{
if (this._dgesvd == null) this._dgesvd = new DGESVD();
Matrix ACopy = A.Clone();
double[] ACopyData = ACopy.Data;
S = new Vector(Math.Min(A.RowCount, A.ColumnCount));// (output) DOUBLE PRECISION array, dimension (min(M,N))
double[] SingularValuesData = S.Data;
Matrix U = new Matrix(1, 1); // A is MxN, U is MxM, como aqui no se requiere no importa
double[] UData = U.Data;
Matrix VT = new Matrix(1, 1);// A is MxN, V is NxN, como aqui no se requiere no importa
double[] VTData = VT.Data;
double[] Work = new double[1];
int LWork = -1;
int Info = 0;
//Calculamos LWORK
this._dgesvd.Run("N", "N", A.RowCount, A.ColumnCount, ref ACopyData, 0, A.RowCount, ref SingularValuesData, 0, ref UData, 0, U.RowCount, ref VTData, 0, VT.RowCount, ref Work, 0, LWork, ref Info);
LWork = Convert.ToInt32(Work[0]);
if (LWork > 0)
{
Work = new double[LWork];
_dgesvd.Run("N", "N", A.RowCount, A.ColumnCount, ref ACopyData, 0, A.RowCount, ref SingularValuesData, 0, ref UData, 0, U.RowCount, ref VTData, 0, VT.RowCount, ref Work, 0, LWork, ref Info);
}
else
{
//Error
}
#region Error
// <param name="INFO">
// (output) INTEGER
// = 0: successful exit.
// .LT. 0: if INFO = -i, the i-th argument had an illegal value.
// .GT. 0: if DBDSQR did not converge, INFO specifies how many
// superdiagonals of an intermediate bidiagonal form B
// did not converge to zero. See the description of WORK
// above for details.
if (Info < 0)
{
string infoSTg = Math.Abs(Info).ToString();
throw new ArgumentException("the " + infoSTg + " -th argument had an illegal value");
}
else if (Info > 0)
{
string infoSTg = Math.Abs(Info).ToString();
throw new Exception("DBDSQR did not converge.");
}
#endregion
}
/// <summary>
///Computes the singular value decomposition (SVD) of a real
/// M-by-N matrix A.
/// The SVD is written
/// A = U * S * transpose(V)
/// </summary>
/// <param name="A">The A matrix.</param>
/// <param name="S">The diagonal elements of S are the singular values of A.</param>
/// <param name="U">The U matrix, U is an M-by-M orthogonal matrix</param>
/// <param name="VT">the transpose(V), V is an N-by-N orthogonal matrix.</param>
public void ComputeSVD(Matrix A, out Matrix S, out Matrix U, out Matrix VT)
{
if (this._dgesvd == null) this._dgesvd = new DGESVD();
Matrix ACopy = A.Clone();
double[] ACopyData = ACopy.Data;
S = new Matrix(A.RowCount, A.ColumnCount);// A is MxN, S is MxN
double[] SingularValuesData = new double[Math.Min(A.RowCount, A.ColumnCount)];
U = new Matrix(A.RowCount, A.RowCount); // A is MxN, U is MxM
double[] UData = U.Data;
VT = new Matrix(A.ColumnCount, A.ColumnCount);// A is MxN, V is NxN
double[] VTData = VT.Data;
double[] Work = new double[1];
int LWork = -1;
int Info = 0;
//Calculamos LWORK
this._dgesvd.Run("A", "A", A.RowCount, A.ColumnCount, ref ACopyData, 0, A.RowCount, ref SingularValuesData, 0, ref UData, 0, U.RowCount, ref VTData, 0, VT.RowCount, ref Work, 0, LWork, ref Info);
LWork = Convert.ToInt32(Work[0]);
if (LWork > 0)
{
Work = new double[LWork];
_dgesvd.Run("A", "A", A.RowCount, A.ColumnCount, ref ACopyData, 0, A.RowCount, ref SingularValuesData, 0, ref UData, 0, U.RowCount, ref VTData, 0, VT.RowCount, ref Work, 0, LWork, ref Info);
}
else
{
//Error
}
#region Error
// <param name="INFO">
// (output) INTEGER
// = 0: successful exit.
// .LT. 0: if INFO = -i, the i-th argument had an illegal value.
// .GT. 0: if DBDSQR did not converge, INFO specifies how many
// superdiagonals of an intermediate bidiagonal form B
// did not converge to zero. See the description of WORK
// above for details.
if (Info < 0)
{
string infoSTg = Math.Abs(Info).ToString();
throw new ArgumentException("the " + infoSTg + " -th argument had an illegal value");
}
else if (Info > 0)
{
string infoSTg = Math.Abs(Info).ToString();
throw new Exception("DBDSQR did not converge.");
}
#endregion
for (int i = 0; i < SingularValuesData.Length; i++)
{
S[i, i] = SingularValuesData[i];
}
}
#endregion
}
}
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