forked from tsai/mathnet-numerics
Jurgen Van Gael
17 years ago
committed by
Christoph Ruegg
Christoph Ruegg
10 changed files with 572 additions and 103 deletions
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// <copyright file="LUTests.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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//
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// Copyright (c) 2009-2010 Math.NET
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//
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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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//
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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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//
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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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namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization |
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{ |
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using System.Collections.Generic; |
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using MbUnit.Framework; |
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using LinearAlgebra.Double; |
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using LinearAlgebra.Double.Factorization; |
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public class LUTests |
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{ |
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[Test] |
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[Row(1)] |
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[Row(10)] |
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[Row(100)] |
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public void CanFactorizeIdentity(int order) |
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{ |
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var I = DenseMatrix.Identity(order); |
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var lu = I.LU(); |
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// Check lower triangular part.
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var L = lu.L; |
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Assert.AreEqual(I.RowCount, L.RowCount); |
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Assert.AreEqual(I.ColumnCount, L.ColumnCount); |
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for (var i = 0; i < L.RowCount; i++) |
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{ |
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for (var j = 0; j < L.ColumnCount; j++) |
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{ |
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if (i == j) |
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{ |
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Assert.AreEqual(1.0, L[i, j]); |
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} |
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else |
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{ |
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Assert.AreEqual(0.0, L[i, j]); |
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} |
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} |
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} |
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// Check upper triangular part.
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var U = lu.U; |
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Assert.AreEqual(I.RowCount, U.RowCount); |
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Assert.AreEqual(I.ColumnCount, U.ColumnCount); |
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for (var i = 0; i < U.RowCount; i++) |
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{ |
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for (var j = 0; j < U.ColumnCount; j++) |
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{ |
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if (i == j) |
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{ |
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Assert.AreEqual(1.0, U[i, j]); |
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} |
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else |
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{ |
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Assert.AreEqual(0.0, U[i, j]); |
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} |
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} |
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} |
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} |
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[Test] |
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[Row(3,5)] |
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[Row(5,3)] |
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[ExpectedArgumentException] |
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public void LUFailsWithNonSquareMatrix(int row, int col) |
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{ |
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var I = new DenseMatrix(row, col); |
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var lu = I.LU(); |
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} |
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[Test] |
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[Row(1)] |
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[Row(10)] |
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[Row(100)] |
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public void IdentityDeterminantIsOne(int order) |
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{ |
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var I = DenseMatrix.Identity(order); |
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var lu = I.LU(); |
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Assert.AreEqual(1.0, lu.Determinant); |
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} |
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[Test] |
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[Row(1)] |
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[Row(2)] |
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[Row(5)] |
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[Row(10)] |
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[Row(50)] |
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[Row(100)] |
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[MultipleAsserts] |
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public void CanFactorizeRandomMatrix(int order) |
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{ |
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var X = MatrixLoader.GenerateRandomMatrix(order, order); |
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var lu = X.LU(); |
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var L = lu.L; |
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var U = lu.U; |
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// Make sure the factors have the right dimensions.
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Assert.AreEqual(order, L.RowCount); |
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Assert.AreEqual(order, L.ColumnCount); |
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Assert.AreEqual(order, U.RowCount); |
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Assert.AreEqual(order, U.ColumnCount); |
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// Make sure the L factor is lower triangular.
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for (int i = 0; i < L.RowCount; i++) |
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{ |
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Assert.AreEqual(1.0, L[i, i]); |
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for (int j = i+1; j < L.ColumnCount; j++) |
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{ |
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Assert.AreEqual(0.0, L[i, j]); |
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} |
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} |
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// Make sure the U factor is upper triangular.
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for (int i = 0; i < L.RowCount; i++) |
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{ |
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for (int j = 0; j < i; j++) |
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{ |
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Assert.AreEqual(0.0, U[i, j]); |
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} |
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} |
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// Make sure the cholesky factor times it's transpose is the original matrix.
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var XfromLU = L * U; |
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lu.Pivot(XfromLU); |
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for (int i = 0; i < XfromLU.RowCount; i++) |
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{ |
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for (int j = 0; j < XfromLU.ColumnCount; j++) |
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{ |
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Assert.AreApproximatelyEqual(X[i, j], XfromLU[i, j], 1.0e-11); |
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} |
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} |
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} |
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/*[Test] |
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[Row(1)] |
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[Row(2)] |
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[Row(5)] |
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[Row(10)] |
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[Row(50)] |
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[Row(100)] |
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[MultipleAsserts] |
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public void CanSolveForRandomVector(int order) |
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{ |
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var A = MatrixLoader.GenerateRandomPositiveDefiniteMatrix(order); |
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var ACopy = A.Clone(); |
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var chol = A.Cholesky(); |
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var b = MatrixLoader.GenerateRandomVector(order); |
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var x = chol.Solve(b); |
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Assert.AreEqual(b.Count, x.Count); |
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var bReconstruct = A * x; |
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// Check the reconstruction.
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for (int i = 0; i < order; i++) |
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{ |
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Assert.AreApproximatelyEqual(b[i], bReconstruct[i], 1.0e-11); |
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} |
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// Make sure A didn't change.
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for (int i = 0; i < A.RowCount; i++) |
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{ |
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for (int j = 0; j < A.ColumnCount; j++) |
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{ |
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Assert.AreEqual(ACopy[i, j], A[i, j]); |
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} |
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} |
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} |
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[Test] |
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[Row(1,1)] |
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[Row(2,4)] |
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[Row(5,8)] |
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[Row(10,3)] |
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[Row(50,10)] |
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[Row(100,100)] |
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[MultipleAsserts] |
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public void CanSolveForRandomMatrix(int row, int col) |
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{ |
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var A = MatrixLoader.GenerateRandomPositiveDefiniteMatrix(row); |
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var ACopy = A.Clone(); |
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var chol = A.Cholesky(); |
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var B = MatrixLoader.GenerateRandomMatrix(row, col); |
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var X = chol.Solve(B); |
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Assert.AreEqual(B.RowCount, X.RowCount); |
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Assert.AreEqual(B.ColumnCount, X.ColumnCount); |
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var BReconstruct = A * X; |
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// Check the reconstruction.
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for (int i = 0; i < B.RowCount; i++) |
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{ |
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for (int j = 0; j < B.ColumnCount; j++) |
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{ |
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Assert.AreApproximatelyEqual(B[i, j], BReconstruct[i, j], 1.0e-11); |
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} |
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} |
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// Make sure A didn't change.
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for (int i = 0; i < A.RowCount; i++) |
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{ |
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for (int j = 0; j < A.ColumnCount; j++) |
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{ |
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Assert.AreEqual(ACopy[i, j], A[i, j]); |
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} |
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} |
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} |
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[Test] |
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[Row(1)] |
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[Row(2)] |
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[Row(5)] |
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[Row(10)] |
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[Row(50)] |
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[Row(100)] |
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[MultipleAsserts] |
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public void CanSolveForRandomVectorWhenResultVectorGiven(int order) |
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{ |
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var A = MatrixLoader.GenerateRandomPositiveDefiniteMatrix(order); |
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var ACopy = A.Clone(); |
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var chol = A.Cholesky(); |
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var b = MatrixLoader.GenerateRandomVector(order); |
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var bCopy = b.Clone(); |
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var x = new DenseVector(order); |
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chol.Solve(b, x); |
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Assert.AreEqual(b.Count, x.Count); |
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var bReconstruct = A * x; |
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// Check the reconstruction.
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for (int i = 0; i < order; i++) |
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{ |
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Assert.AreApproximatelyEqual(b[i], bReconstruct[i], 1.0e-11); |
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} |
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// Make sure A didn't change.
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for (int i = 0; i < A.RowCount; i++) |
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{ |
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for (int j = 0; j < A.ColumnCount; j++) |
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{ |
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Assert.AreEqual(ACopy[i, j], A[i, j]); |
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} |
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} |
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// Make sure b didn't change.
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for (int i = 0; i < order; i++) |
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{ |
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Assert.AreEqual(bCopy[i], b[i]); |
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} |
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} |
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[Test] |
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[Row(1, 1)] |
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[Row(2, 4)] |
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[Row(5, 8)] |
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[Row(10, 3)] |
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[Row(50, 10)] |
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[Row(100, 100)] |
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[MultipleAsserts] |
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public void CanSolveForRandomMatrixWhenResultMatrixGiven(int row, int col) |
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{ |
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var A = MatrixLoader.GenerateRandomPositiveDefiniteMatrix(row); |
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var ACopy = A.Clone(); |
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var chol = A.Cholesky(); |
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var B = MatrixLoader.GenerateRandomMatrix(row, col); |
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var BCopy = B.Clone(); |
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var X = new DenseMatrix(row, col); |
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chol.Solve(B, X); |
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Assert.AreEqual(B.RowCount, X.RowCount); |
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Assert.AreEqual(B.ColumnCount, X.ColumnCount); |
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var BReconstruct = A * X; |
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// Check the reconstruction.
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for (int i = 0; i < B.RowCount; i++) |
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{ |
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for (int j = 0; j < B.ColumnCount; j++) |
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{ |
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Assert.AreApproximatelyEqual(B[i, j], BReconstruct[i, j], 1.0e-11); |
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} |
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} |
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// Make sure A didn't change.
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for (int i = 0; i < A.RowCount; i++) |
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{ |
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for (int j = 0; j < A.ColumnCount; j++) |
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{ |
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Assert.AreEqual(ACopy[i, j], A[i, j]); |
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} |
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} |
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// Make sure B didn't change.
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for (int i = 0; i < B.RowCount; i++) |
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{ |
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for (int j = 0; j < B.ColumnCount; j++) |
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{ |
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Assert.AreEqual(BCopy[i, j], B[i, j]); |
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} |
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} |
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}*/ |
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} |
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} |
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