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using System;
using IStation.Numerics.Providers.LinearAlgebra;
namespace IStation.Numerics.LinearAlgebra.Double.Factorization
{
///
/// A class which encapsulates the functionality of an LU factorization.
/// For a matrix A, the LU factorization is a pair of lower triangular matrix L and
/// upper triangular matrix U so that A = L*U.
///
///
/// The computation of the LU factorization is done at construction time.
///
internal sealed class DenseLU : LU
{
///
/// Initializes a new instance of the class. This object will compute the
/// LU factorization when the constructor is called and cache it's factorization.
///
/// The matrix to factor.
/// If is null.
/// If is not a square matrix.
public static DenseLU Create(DenseMatrix matrix)
{
if (matrix == null)
{
throw new ArgumentNullException(nameof(matrix));
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException("Matrix must be square.");
}
// Create an array for the pivot indices.
var pivots = new int[matrix.RowCount];
// Create a new matrix for the LU factors, then perform factorization (while overwriting).
var factors = (DenseMatrix) matrix.Clone();
LinearAlgebraControl.Provider.LUFactor(factors.Values, factors.RowCount, pivots);
return new DenseLU(factors, pivots);
}
DenseLU(Matrix factors, int[] pivots)
: base(factors, pivots)
{
}
///
/// Solves a system of linear equations, AX = B, with A LU factorized.
///
/// The right hand side , B.
/// The left hand side , X.
public override void Solve(Matrix input, Matrix result)
{
// Check for proper arguments.
if (input == null)
{
throw new ArgumentNullException(nameof(input));
}
if (result == null)
{
throw new ArgumentNullException(nameof(result));
}
// Check for proper dimensions.
if (result.RowCount != input.RowCount)
{
throw new ArgumentException("Matrix row dimensions must agree.");
}
if (result.ColumnCount != input.ColumnCount)
{
throw new ArgumentException("Matrix column dimensions must agree.");
}
if (input.RowCount != Factors.RowCount)
{
throw Matrix.DimensionsDontMatch(input, Factors);
}
if (input is DenseMatrix dinput && result is DenseMatrix dresult)
{
// Copy the contents of input to result.
Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfDouble);
// LU solve by overwriting result.
var dfactors = (DenseMatrix) Factors;
LinearAlgebraControl.Provider.LUSolveFactored(input.ColumnCount, dfactors.Values, dfactors.RowCount, Pivots, dresult.Values);
}
else
{
throw new NotSupportedException("Can only do LU factorization for dense matrices at the moment.");
}
}
///
/// Solves a system of linear equations, Ax = b, with A LU factorized.
///
/// The right hand side vector, b.
/// The left hand side , x.
public override void Solve(Vector input, Vector result)
{
// Check for proper arguments.
if (input == null)
{
throw new ArgumentNullException(nameof(input));
}
if (result == null)
{
throw new ArgumentNullException(nameof(result));
}
// Check for proper dimensions.
if (input.Count != result.Count)
{
throw new ArgumentException("All vectors must have the same dimensionality.");
}
if (input.Count != Factors.RowCount)
{
throw Matrix.DimensionsDontMatch(input, Factors);
}
if (input is DenseVector dinput && result is DenseVector dresult)
{
// Copy the contents of input to result.
Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfDouble);
// LU solve by overwriting result.
var dfactors = (DenseMatrix) Factors;
LinearAlgebraControl.Provider.LUSolveFactored(1, dfactors.Values, dfactors.RowCount, Pivots, dresult.Values);
}
else
{
throw new NotSupportedException("Can only do LU factorization for dense vectors at the moment.");
}
}
///
/// Returns the inverse of this matrix. The inverse is calculated using LU decomposition.
///
/// The inverse of this matrix.
public override Matrix Inverse()
{
var result = (DenseMatrix) Factors.Clone();
LinearAlgebraControl.Provider.LUInverseFactored(result.Values, result.RowCount, Pivots);
return result;
}
}
}