Math.NET Numerics
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// <copyright file="QR.cs" company="Math.NET">
// Math.NET Numerics, part of the Math.NET Project
// http://numerics.mathdotnet.com
// http://github.com/mathnet/mathnet-numerics
//
// Copyright (c) 2009-2013 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.
// </copyright>
using System;
using MathNet.Numerics.LinearAlgebra.Factorization;
using MathNet.Numerics.Properties;
namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
{
/// <summary>
/// <para>A class which encapsulates the functionality of the QR decomposition.</para>
/// <para>Any real square matrix A (m x n) may be decomposed as A = QR where Q is an orthogonal matrix
/// (its columns are orthogonal unit vectors meaning QTQ = I) and R is an upper triangular matrix
/// (also called right triangular matrix).</para>
/// </summary>
/// <remarks>
/// The computation of the QR decomposition is done at construction time by Householder transformation.
/// If a <seealso cref="QRMethod.Full"/> factorization is performed, the resulting Q matrix is an m x m matrix
/// and the R matrix is an m x n matrix. If a <seealso cref="QRMethod.Thin"/> factorization is performed, the
/// resulting Q matrix is an m x n matrix and the R matrix is an n x n matrix.
/// </remarks>
internal abstract class QR : QR<float>
{
protected QR(Matrix<float> q, Matrix<float> rFull, QRMethod method)
: base(q, rFull, method)
{
}
/// <summary>
/// Gets the absolute determinant value of the matrix for which the QR matrix was computed.
/// </summary>
public override float Determinant
{
get
{
if (FullR.RowCount != FullR.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare);
}
var det = 1.0;
for (var i = 0; i < FullR.ColumnCount; i++)
{
det *= FullR.At(i, i);
if (Math.Abs(FullR.At(i, i)).AlmostEqual(0.0f))
{
return 0;
}
}
return Convert.ToSingle(Math.Abs(det));
}
}
/// <summary>
/// Gets a value indicating whether the matrix is full rank or not.
/// </summary>
/// <value><c>true</c> if the matrix is full rank; otherwise <c>false</c>.</value>
public override bool IsFullRank
{
get
{
for (var i = 0; i < FullR.ColumnCount; i++)
{
if (Math.Abs(FullR.At(i, i)).AlmostEqual(0.0f))
{
return false;
}
}
return true;
}
}
}
}