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131 lines
5.7 KiB
131 lines
5.7 KiB
// <copyright file="QR.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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// Copyright (c) 2009-2010 Math.NET
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System;
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using System.Globalization;
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using MathNet.Numerics.LinearAlgebra.Double;
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namespace Examples.LinearAlgebra.FactorizationExamples
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{
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/// <summary>
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/// QR factorization example. Any real square matrix A (m x n) may be decomposed as A = QR where Q is an orthogonal matrix (m x m)
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/// (its columns are orthogonal unit vectors meaning QTQ = I) and R (m x n) is an upper triangular matrix
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/// (also called right triangular matrix).
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/// In this example two methods for actually computing the QR decomposition presented: by means of the Gram–Schmidt process and Householder transformations.
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/// </summary>
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/// <seealso cref="http://reference.wolfram.com/mathematica/ref/QRDecomposition.html"/>
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public class QR : IExample
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{
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/// <summary>
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/// Gets the name of this example
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/// </summary>
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public string Name
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{
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get
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{
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return "QR factorization";
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}
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}
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/// <summary>
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/// Gets the description of this example
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/// </summary>
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public string Description
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{
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get
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{
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return "Perform the QR factorization by means of the Gram–Schmidt process and Householder transformations";
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}
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}
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/// <summary>
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/// Run example
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/// </summary>
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/// <seealso cref="http://en.wikipedia.org/wiki/QR_decomposition">QR decomposition</seealso>
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public void Run()
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{
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// Format matrix output to console
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var formatProvider = (CultureInfo)CultureInfo.InvariantCulture.Clone();
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formatProvider.TextInfo.ListSeparator = " ";
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// Create 3 x 2 matrix
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var matrix = DenseMatrix.OfArray(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 }, { 5.0, 6.0 } });
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Console.WriteLine(@"Initial 3x2 matrix");
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Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// Perform QR decomposition (Householder transformations)
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var qr = matrix.QR();
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Console.WriteLine(@"QR decomposition (Householder transformations)");
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// 1. Orthogonal Q matrix
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Console.WriteLine(@"1. Orthogonal Q matrix");
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Console.WriteLine(qr.Q.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 2. Multiply Q matrix by its transpose gives identity matrix
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Console.WriteLine(@"2. Multiply Q matrix by its transpose gives identity matrix");
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Console.WriteLine(qr.Q.TransposeAndMultiply(qr.Q).ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 3. Upper triangular factor R
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Console.WriteLine(@"3. Upper triangular factor R");
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Console.WriteLine(qr.R.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 4. Reconstruct initial matrix: A = Q * R
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var reconstruct = qr.Q * qr.R;
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Console.WriteLine(@"4. Reconstruct initial matrix: A = Q*R");
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Console.WriteLine(reconstruct.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// Perform QR decomposition (Gram–Schmidt process)
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var gramSchmidt = matrix.GramSchmidt();
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Console.WriteLine(@"QR decomposition (Gram–Schmidt process)");
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// 5. Orthogonal Q matrix
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Console.WriteLine(@"5. Orthogonal Q matrix");
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Console.WriteLine(gramSchmidt.Q.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 6. Multiply Q matrix by its transpose gives identity matrix
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Console.WriteLine(@"6. Multiply Q matrix by its transpose gives identity matrix");
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Console.WriteLine((gramSchmidt.Q.Transpose() * gramSchmidt.Q).ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 7. Upper triangular factor R
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Console.WriteLine(@"7. Upper triangular factor R");
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Console.WriteLine(gramSchmidt.R.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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// 8. Reconstruct initial matrix: A = Q * R
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reconstruct = gramSchmidt.Q * gramSchmidt.R;
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Console.WriteLine(@"8. Reconstruct initial matrix: A = Q*R");
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Console.WriteLine(reconstruct.ToString("#0.00\t", formatProvider));
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Console.WriteLine();
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}
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}
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}
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