public override void SingularValueDecomposition(bool computeVectors, <#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt)
{
throw new NotImplementedException();
}
if (a == null)
{
throw new ArgumentNullException("a");
}
/// <summary>
/// Computes the singular value decomposition of A.
/// </summary>
/// <param name="computeVectors">Compute the singular U and VT vectors or not.</param>
/// <param name="a">On entry, the M by N matrix to decompose. On exit, A may be overwritten.</param>
/// <param name="rowsA">The number of rows in the A matrix.</param>
/// <param name="columnsA">The number of columns in the A matrix.</param>
/// <param name="s">The singular values of A in ascending value.</param>
/// <param name="u">If <paramref name="computeVectors"/> is <c>true</c>, on exit U contains the left
/// singular vectors.</param>
/// <param name="vt">If <paramref name="computeVectors"/> is <c>true</c>, on exit VT contains the transposed
/// right singular vectors.</param>
/// <param name="work">The work array. For real matrices, the work array should be at least
/// On exit, work[0] contains the optimal work size value.</param>
/// <remarks>This is equivalent to the GESVD LAPACK routine.</remarks>
[SecuritySafeCritical]
public override void SingularValueDecomposition(bool computeVectors, <#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt, <#=dataType#>[] work)
{
throw new NotImplementedException();
if (s == null)
{
throw new ArgumentNullException("s");
}
if (u == null)
{
throw new ArgumentNullException("u");
}
if (vt == null)
{
throw new ArgumentNullException("vt");
}
if (u.Length != rowsA * rowsA)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "u");
}
if (vt.Length != columnsA * columnsA)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "vt");
}
if (s.Length != Math.Min(rowsA, columnsA))
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "s");
}
var work = new <#=dataType#>[<#=svd_work#>];
SingularValueDecomposition(computeVectors, a, rowsA, columnsA, s, u, vt, work);
}
/// <summary>
/// Solves A*X=B for X using the singular value decomposition of A.
/// </summary>
/// <param name="a">On entry, the M by N matrix to decompose. On exit, A may be overwritten.</param>
/// <param name="a">On entry, the M by N matrix to decompose.</param>
/// <param name="rowsA">The number of rows in the A matrix.</param>
/// <param name="columnsA">The number of columns in the A matrix.</param>
/// <param name="s">The singular values of A in ascending value.</param>
/// <param name="u">On exit U contains the left singular vectors.</param>
/// <param name="vt">On exit VT contains the transposed right singular vectors.</param>
/// <param name="b">The B matrix.</param>
/// <param name="columnsB">The number of columns of B.</param>
/// <param name="x">On exit, the solution matrix.</param>
[SecuritySafeCritical]
public override void SvdSolve(<#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt, <#=dataType#>[] b, int columnsB, <#=dataType#>[] x)
public override void SvdSolve(<#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] b, int columnsB, <#=dataType#>[] x)
{
throw new NotImplementedException();
if (a == null)
{
throw new ArgumentNullException("a");
}
if (b == null)
{
throw new ArgumentNullException("b");
}
if (x == null)
{
throw new ArgumentNullException("x");
}
if (b.Length != rowsA * columnsB)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "b");
}
if (x.Length != columnsA * columnsB)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "b");
}
var work = new <#=dataType#>[<#=svd_work#>];
var s = new <#=dataType#>[Math.Min(rowsA, columnsA)];
/// On exit, work[0] contains the optimal work size value.</param>
/// <remarks>This is equivalent to the GESVD LAPACK routine.</remarks>
[SecuritySafeCritical]
public override void SvdSolve(<#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt, <#=dataType#>[] b, int columnsB, <#=dataType#>[] x, <#=dataType#>[] work)
public override void SingularValueDecomposition(bool computeVectors, <#=dataType#>[] a, int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt, <#=dataType#>[] work)
{
throw new NotImplementedException();
}
if (a == null)
{
throw new ArgumentNullException("a");
}
/// <summary>
/// Solves A*X=B for X using a previously SVD decomposed matrix.
/// </summary>
/// <param name="rowsA">The number of rows in the A matrix.</param>
/// <param name="columnsA">The number of columns in the A matrix.</param>
/// <param name="s">The s values returned by <see cref="SingularValueDecomposition(bool,<#=dataType#>[],int,int,<#=dataType#>[],<#=dataType#>[],<#=dataType#>[])"/>.</param>
/// <param name="u">The left singular vectors returned by <see cref="SingularValueDecomposition(bool,<#=dataType#>[],int,int,<#=dataType#>[],<#=dataType#>[],<#=dataType#>[])"/>.</param>
/// <param name="vt">The right singular vectors returned by <see cref="SingularValueDecomposition(bool,<#=dataType#>[],int,int,<#=dataType#>[],<#=dataType#>[],<#=dataType#>[])"/>.</param>
/// <param name="b">The B matrix.</param>
/// <param name="columnsB">The number of columns of B.</param>
/// <param name="x">On exit, the solution matrix.</param>
[SecuritySafeCritical]
public override void SvdSolveFactored(int rowsA, int columnsA, <#=dataType#>[] s, <#=dataType#>[] u, <#=dataType#>[] vt, <#=dataType#>[] b, int columnsB, <#=dataType#>[] x)
{
throw new NotImplementedException();
if (s == null)
{
throw new ArgumentNullException("s");
}
if (u == null)
{
throw new ArgumentNullException("u");
}
if (vt == null)
{
throw new ArgumentNullException("vt");
}
if (work == null)
{
throw new ArgumentNullException("work");
}
if (u.Length != rowsA * rowsA)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "u");
}
if (vt.Length != columnsA * columnsA)
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "vt");
}
if (s.Length != Math.Min(rowsA, columnsA))
{
throw new ArgumentException(Resources.ArgumentArraysSameLength, "s");
}
if (work.Length == 0)
{
throw new ArgumentException(Resources.ArgumentSingleDimensionArray, "work");
}
if (work.Length < <#=svd_work#>)
{
work[0] = <#=svd_work#>;
throw new ArgumentException(Resources.WorkArrayTooSmall, "work");
}
SafeNativeMethods.<#=prefix#>_svd_factor(computeVectors, rowsA, columnsA, a, s, u, vt, work, work.Length);
internal static extern int z_qr_solve_factored(int m, int n, int bn, Complex[] r, Complex[] b, Complex[] tau, [In, Out] Complex[] x, [In, Out] Complex[] work, int len);
internal static extern int s_svd_factor(bool compute_vectors, int m, int n, [In, Out] float[] a, [In, Out] float[] s, [In, Out] float[] u, [In, Out] float[] v, [In, Out] float[] work, int len);
internal static extern int d_svd_factor(bool compute_vectors, int m, int n, [In, Out] double[] a, [In, Out] double[] s, [In, Out] double[] u, [In, Out] double[] v, [In, Out] double[] work, int len);
internal static extern int c_svd_factor(bool compute_vectors, int m, int n, [In, Out] Complex32[] a, [In, Out] Complex32[] s, [In, Out] Complex32[] u, [In, Out] Complex32[] v, [In, Out] Complex32[] work, int len);
internal static extern int z_svd_factor(bool compute_vectors, int m, int n, [In, Out] Complex[] a, [In, Out] Complex[] s, [In, Out] Complex[] u, [In, Out] Complex[] v, [In, Out] Complex[] work, int len);
Marcus Cuda
16 years ago