namespace Mapack
{
using System;
/// Cholesky Decomposition of a symmetric, positive definite matrix.
///
/// For a symmetric, positive definite matrix A, the Cholesky decomposition is a
/// lower triangular matrix L so that A = L * L'.
/// If the matrix is not symmetric or positive definite, the constructor returns a partial
/// decomposition and sets two internal variables that can be queried using the
/// and properties.
///
public class CholeskyDecomposition
{
private Matrix L;
private bool symmetric;
private bool positiveDefinite;
/// Construct a Cholesky Decomposition.
public CholeskyDecomposition(Matrix value)
{
if (value == null)
{
throw new ArgumentNullException("value");
}
if (!value.Square)
{
throw new ArgumentException("Matrix is not square.", "value");
}
int dimension = value.Rows;
L = new Matrix(dimension, dimension);
double[][] a = value.Array;
double[][] l = L.Array;
this.positiveDefinite = true;
this.symmetric = true;
for (int j = 0; j < dimension; j++)
{
double[] Lrowj = l[j];
double d = 0.0;
for (int k = 0; k < j; k++)
{
double[] Lrowk = l[k];
double s = 0.0;
for (int i = 0; i < k; i++)
{
s += Lrowk[i] * Lrowj[i];
}
Lrowj[k] = s = (a[j][k] - s) / l[k][k];
d = d + s*s;
this.symmetric = this.symmetric & (a[k][j] == a[j][k]);
}
d = a[j][j] - d;
this.positiveDefinite = this.positiveDefinite & (d > 0.0);
l[j][j] = Math.Sqrt(Math.Max(d,0.0));
for (int k = j + 1; k < dimension; k++)
{
l[j][k] = 0.0;
}
}
}
/// Returns if the matrix is symmetric.
public bool Symmetric
{
get
{
return this.symmetric;
}
}
/// Returns if the matrix is positive definite.
public bool PositiveDefinite
{
get
{
return this.positiveDefinite;
}
}
/// Returns the left triangular factor L so that A = L * L'.
public Matrix LeftTriangularFactor
{
get
{
return this.L;
}
}
/// Solves a set of equation systems of type A * X = B.
/// Right hand side matrix with as many rows as A and any number of columns.
/// Matrix X so that L * L' * X = B.
/// Matrix dimensions do not match.
/// Matrix is not symmetrix and positive definite.
public Matrix Solve(Matrix value)
{
if (value == null)
{
throw new ArgumentNullException("value");
}
if (value.Rows != L.Rows)
{
throw new ArgumentException("Matrix dimensions do not match.");
}
if (!this.symmetric)
{
throw new InvalidOperationException("Matrix is not symmetric.");
}
if (!this.positiveDefinite)
{
throw new InvalidOperationException("Matrix is not positive definite.");
}
// Solve L*Y = B;
int dimension = L.Rows;
int count = value.Columns;
Matrix B = (Matrix)value.Clone();
double[][] l = L.Array;
// Solve L*Y = B;
for (int k = 0; k < dimension; k++)
{
for (int j = 0; j < count; j++)
{
for (int i = 0; i < k; i++)
{
B[k, j] -= B[i, j] * l[k][i];
}
B[k, j] /= l[k][k];
}
}
// Solve L'*X = Y;
for (int k = dimension - 1; k >= 0; k--)
{
for (int j = 0; j < count; j++)
{
for (int i = k + 1; i < dimension; i++)
{
B[k, j] -= B[i, j] * L[i, k];
}
B[k, j] /= l[k][k];
}
}
return B;
}
}
}