/// <summary>
/// Constructs a new Cholesky Decomposition.
/// </summary>
///
/// <param name="value">
/// The symmetric matrix, given in upper triangular form, to be decomposed.</param>
/// <param name="robust">
/// True to perform a square-root free LDLt decomposition, false otherwise.</param>
/// <param name="inPlace">
/// True to perform the decomposition in place, storing the factorization in the
/// lower triangular part of the given matrix.</param>
/// <param name="valueType">
/// How to interpret the matrix given to be decomposed. Using this parameter, a lower or
/// upper-triangular matrix can be interpreted as a symmetric matrix by assuming both lower
/// and upper parts contain the same elements. Use this parameter in conjunction with inPlace
/// to save memory by storing the original matrix and its decomposition at the same memory
/// location (lower part will contain the decomposition's L matrix, upper part will contains
/// the original matrix).</param>
///
public CholeskyDecompositionF(Single[,] value, bool robust = false,
bool inPlace = false, MatrixType valueType = MatrixType.UpperTriangular)
{
if (value.Rows() != value.Columns())
{
throw new DimensionMismatchException("value", "Matrix is not square.");
}
if (!inPlace)
{
value = value.Copy();
}
this.n = value.Rows();
this.L = value.ToUpperTriangular(valueType, result: value);
this.robust = robust;
if (robust)
{
LDLt(); // Compute square-root free decomposition
}
else
{
LLt(); // Compute standard Cholesky decomposition
}
}