// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // http://mathnetnumerics.codeplex.com // // Copyright (c) 2009-2010 Math.NET // // Permission is hereby granted, free of charge, to any person // obtaining a copy of this software and associated documentation // files (the "Software"), to deal in the Software without // restriction, including without limitation the rights to use, // copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the // Software is furnished to do so, subject to the following // conditions: // // The above copyright notice and this permission notice shall be // included in all copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR // OTHER DEALINGS IN THE SOFTWARE. // using MathNet.Numerics.Properties; using System; namespace MathNet.Numerics.LinearAlgebra.Single.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. /// public class UserLU : 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 UserLU(Matrix matrix) { if (matrix == null) { throw new ArgumentNullException("matrix"); } if (matrix.RowCount != matrix.ColumnCount) { throw new ArgumentException(Resources.ArgumentMatrixSquare); } // Create an array for the pivot indices. var order = matrix.RowCount; Factors = matrix.Clone(); Pivots = new int[order]; // Initialize the pivot matrix to the identity permutation. for (var i = 0; i < order; i++) { Pivots[i] = i; } var vectorLUcolj = new float[order]; for (var j = 0; j < order; j++) { // Make a copy of the j-th column to localize references. for (var i = 0; i < order; i++) { vectorLUcolj[i] = Factors.At(i, j); } // Apply previous transformations. for (var i = 0; i < order; i++) { var kmax = Math.Min(i, j); var s = 0.0f; for (var k = 0; k < kmax; k++) { s += Factors.At(i, k) * vectorLUcolj[k]; } vectorLUcolj[i] -= s; Factors.At(i, j, vectorLUcolj[i]); } // Find pivot and exchange if necessary. var p = j; for (var i = j + 1; i < order; i++) { if (Math.Abs(vectorLUcolj[i]) > Math.Abs(vectorLUcolj[p])) { p = i; } } if (p != j) { for (var k = 0; k < order; k++) { var temp = Factors.At(p, k); Factors.At(p, k, Factors.At(j, k)); Factors.At(j, k, temp); } Pivots[j] = p; } // Compute multipliers. if (j < order & Factors.At(j, j) != 0.0) { for (var i = j + 1; i < order; i++) { Factors.At(i, j, (Factors.At(i, j) / Factors.At(j, j))); } } } } /// /// 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("input"); } if (result == null) { throw new ArgumentNullException("result"); } // Check for proper dimensions. if (result.RowCount != input.RowCount) { throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension); } if (result.ColumnCount != input.ColumnCount) { throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension); } if (input.RowCount != Factors.RowCount) { throw Matrix.DimensionsDontMatch(input, Factors); } // Copy the contents of input to result. input.CopyTo(result); for (var i = 0; i < Pivots.Length; i++) { if (Pivots[i] == i) { continue; } var p = Pivots[i]; for (var j = 0; j < result.ColumnCount; j++) { var temp = result.At(p, j); result.At(p, j, result.At(i, j)); result.At(i, j, temp); } } var order = Factors.RowCount; // Solve L*Y = P*B for (var k = 0; k < order; k++) { for (var i = k + 1; i < order; i++) { for (var j = 0; j < result.ColumnCount; j++) { var temp = result.At(k, j) * Factors.At(i, k); result.At(i, j, result.At(i, j) - temp); } } } // Solve U*X = Y; for (var k = order - 1; k >= 0; k--) { for (var j = 0; j < result.ColumnCount; j++) { result.At(k, j, (result.At(k, j) / Factors.At(k, k))); } for (var i = 0; i < k; i++) { for (var j = 0; j < result.ColumnCount; j++) { var temp = result.At(k, j) * Factors.At(i, k); result.At(i, j, result.At(i, j) - temp); } } } } /// /// 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("input"); } if (result == null) { throw new ArgumentNullException("result"); } // Check for proper dimensions. if (input.Count != result.Count) { throw new ArgumentException(Resources.ArgumentVectorsSameLength); } if (input.Count != Factors.RowCount) { throw Matrix.DimensionsDontMatch(input, Factors); } // Copy the contents of input to result. input.CopyTo(result); for (var i = 0; i < Pivots.Length; i++) { if (Pivots[i] == i) { continue; } var p = Pivots[i]; var temp = result[p]; result[p] = result[i]; result[i] = temp; } var order = Factors.RowCount; // Solve L*Y = P*B for (var k = 0; k < order; k++) { for (var i = k + 1; i < order; i++) { result[i] -= result[k] * Factors.At(i, k); } } // Solve U*X = Y; for (var k = order - 1; k >= 0; k--) { result[k] /= Factors.At(k, k); for (var i = 0; i < k; i++) { result[i] -= result[k] * Factors.At(i, k); } } } /// /// Returns the inverse of this matrix. The inverse is calculated using LU decomposition. /// /// The inverse of this matrix. public override Matrix Inverse() { var order = Factors.RowCount; var inverse = Factors.CreateMatrix(order, order); for (var i = 0; i < order; i++) { inverse.At(i, i, 1.0f); } return Solve(inverse); } } }