public void CanSolveForRandomVectorAndSymmetricMatrix(int order)
{
var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var vectorb = MatrixLoader.GenerateRandomDenseVector(order);
var resultx = factorEvd.Solve(vectorb);
Assert.AreEqual(matrixA.ColumnCount, resultx.Count);
var matrixBReconstruct = matrixA * resultx;
// Check the reconstruction.
for (var i = 0; i < vectorb.Count; i++)
{
Assert.AreEqual(vectorb[i].Real, matrixBReconstruct[i].Real, 1e-3f);
Assert.AreEqual(vectorb[i].Imaginary, matrixBReconstruct[i].Imaginary, 1e-3f);
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
}
public void CanSolveForRandomMatrixAndSymmetricMatrixWhenResultMatrixGiven([Values(1, 2, 5, 10, 50, 100)] int order)
{
var A = new UserDefinedMatrix(Matrix <Complex> .Build.RandomPositiveDefinite(order, 1).ToArray());
MatrixHelpers.ForceConjugateSymmetric(A);
var ACopy = A.Clone();
var evd = A.Evd();
var B = new UserDefinedMatrix(Matrix <Complex> .Build.Random(order, order, 1).ToArray());
var BCopy = B.Clone();
var X = new UserDefinedMatrix(order, order);
evd.Solve(B, X);
// The solution X row dimension is equal to the column dimension of A
Assert.AreEqual(A.ColumnCount, X.RowCount);
// The solution X has the same number of columns as B
Assert.AreEqual(B.ColumnCount, X.ColumnCount);
var BReconstruct = A * X;
// Check the reconstruction.
AssertHelpers.AlmostEqual(B, BReconstruct, 9);
// Make sure A/B didn't change.
AssertHelpers.AlmostEqual(ACopy, A, 14);
AssertHelpers.AlmostEqual(BCopy, B, 14);
}
public void CanFactorizeRandomSymmetricMatrix([Values(1, 2, 5, 10)] int order)
{
var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var factorEvd = matrixA.Evd();
var eigenVectors = factorEvd.EigenVectors;
var d = factorEvd.D;
Assert.AreEqual(order, eigenVectors.RowCount);
Assert.AreEqual(order, eigenVectors.ColumnCount);
Assert.AreEqual(order, d.RowCount);
Assert.AreEqual(order, d.ColumnCount);
// Make sure the A = V*λ*VT
var matrix = eigenVectors * d * eigenVectors.ConjugateTranspose();
for (var i = 0; i < matrix.RowCount; i++)
{
for (var j = 0; j < matrix.ColumnCount; j++)
{
AssertHelpers.AlmostEqualRelative(matrix[i, j], matrixA[i, j], 3);
}
}
}
public void CanSolveForRandomVectorAndSymmetricMatrix(int order)
{
var matrixA = Matrix <Complex> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var vectorb = Vector <Complex> .Build.Random(order, 1);
var resultx = factorEvd.Solve(vectorb);
Assert.AreEqual(matrixA.ColumnCount, resultx.Count);
var matrixBReconstruct = matrixA * resultx;
// Check the reconstruction.
for (var i = 0; i < vectorb.Count; i++)
{
AssertHelpers.AlmostEqual(vectorb[i], matrixBReconstruct[i], 10);
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
}
public void CanSolveForRandomVectorAndSymmetricMatrixWhenResultVectorGiven([Values(1, 2, 5, 10, 50, 100)] int order)
{
var A = Matrix <Complex32> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(A);
var ACopy = A.Clone();
var evd = A.Evd();
var b = Vector <Complex32> .Build.Random(order, 2);
var bCopy = b.Clone();
var x = new DenseVector(order);
evd.Solve(b, x);
var bReconstruct = A * x;
// Check the reconstruction.
AssertHelpers.AlmostEqual(b, bReconstruct, 2);
// Make sure A/B didn't change.
AssertHelpers.AlmostEqual(ACopy, A, 14);
AssertHelpers.AlmostEqual(bCopy, b, 14);
}
public void CanFactorizeRandomSymmetricMatrix(int order)
{
var matrixA = Matrix <Complex> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var factorEvd = matrixA.Evd();
var eigenVectors = factorEvd.EigenVectors;
var d = factorEvd.D;
Assert.AreEqual(order, eigenVectors.RowCount);
Assert.AreEqual(order, eigenVectors.ColumnCount);
Assert.AreEqual(order, d.RowCount);
Assert.AreEqual(order, d.ColumnCount);
// Make sure the A = V*λ*VT
var matrix = eigenVectors * d * eigenVectors.ConjugateTranspose();
for (var i = 0; i < matrix.RowCount; i++)
{
for (var j = 0; j < matrix.ColumnCount; j++)
{
AssertHelpers.AlmostEqualRelative(matrix[i, j], matrixA[i, j], 7);
}
}
}
public void CanSolveForRandomMatrixAndSymmetricMatrixWhenResultMatrixGiven(int order)
{
var matrixA = Matrix <Complex32> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var matrixB = Matrix <Complex32> .Build.Random(order, order, 1);
var matrixBCopy = matrixB.Clone();
var matrixX = new DenseMatrix(order, order);
factorEvd.Solve(matrixB, matrixX);
// The solution X row dimension is equal to the column dimension of A
Assert.AreEqual(matrixA.ColumnCount, matrixX.RowCount);
// The solution X has the same number of columns as B
Assert.AreEqual(matrixB.ColumnCount, matrixX.ColumnCount);
var matrixBReconstruct = matrixA * matrixX;
// Check the reconstruction.
for (var i = 0; i < matrixB.RowCount; i++)
{
for (var j = 0; j < matrixB.ColumnCount; j++)
{
Assert.AreEqual(matrixB[i, j].Real, matrixBReconstruct[i, j].Real, 1e-2f);
Assert.AreEqual(matrixB[i, j].Imaginary, matrixBReconstruct[i, j].Imaginary, 1e-2f);
}
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
// Make sure B didn't change.
for (var i = 0; i < matrixB.RowCount; i++)
{
for (var j = 0; j < matrixB.ColumnCount; j++)
{
Assert.AreEqual(matrixBCopy[i, j], matrixB[i, j]);
}
}
}
public void CanFactorizeRandomSymmetricMatrix([Values(1, 2, 5, 10, 50, 100)] int order)
{
var A = Matrix <Complex32> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(A);
var factorEvd = A.Evd();
var V = factorEvd.EigenVectors;
var λ = factorEvd.D;
Assert.AreEqual(order, V.RowCount);
Assert.AreEqual(order, V.ColumnCount);
Assert.AreEqual(order, λ.RowCount);
Assert.AreEqual(order, λ.ColumnCount);
// Verify A = V*λ*VT
var matrix = V * λ * V.ConjugateTranspose();
AssertHelpers.AlmostEqual(matrix, A, 3);
AssertHelpers.AlmostEqualRelative(matrix, A, 1);
}
public void CanSolveForRandomVectorAndSymmetricMatrix([Values(1, 2, 5, 10, 50, 100)] int order)
{
var A = new UserDefinedMatrix(Matrix <Complex> .Build.RandomPositiveDefinite(order, 1).ToArray());
MatrixHelpers.ForceConjugateSymmetric(A);
var ACopy = A.Clone();
var evd = A.Evd();
var b = new UserDefinedVector(Vector <Complex> .Build.Random(order, 1).ToArray());
var bCopy = b.Clone();
var x = evd.Solve(b);
var bReconstruct = A * x;
// Check the reconstruction.
AssertHelpers.AlmostEqual(b, bReconstruct, 9);
// Make sure A/B didn't change.
AssertHelpers.AlmostEqual(ACopy, A, 14);
AssertHelpers.AlmostEqual(bCopy, b, 14);
}
public void CanSolveForRandomVectorAndSymmetricMatrixWhenResultVectorGiven(int order)
{
var matrixA = Matrix <Complex32> .Build.RandomPositiveDefinite(order, 1);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var vectorb = Vector <Complex32> .Build.Random(order, 1);
var vectorbCopy = vectorb.Clone();
var resultx = new DenseVector(order);
factorEvd.Solve(vectorb, resultx);
var matrixBReconstruct = matrixA * resultx;
// Check the reconstruction.
for (var i = 0; i < vectorb.Count; i++)
{
Assert.AreEqual(vectorb[i].Real, matrixBReconstruct[i].Real, 1e-3f);
Assert.AreEqual(vectorb[i].Imaginary, matrixBReconstruct[i].Imaginary, 1e-3f);
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
// Make sure b didn't change.
for (var i = 0; i < vectorb.Count; i++)
{
Assert.AreEqual(vectorbCopy[i], vectorb[i]);
}
}
public void CanSolveForRandomMatrixAndSymmetricMatrix(int order)
{
var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var matrixB = MatrixLoader.GenerateRandomDenseMatrix(order, order);
var matrixX = factorEvd.Solve(matrixB);
// The solution X row dimension is equal to the column dimension of A
Assert.AreEqual(matrixA.ColumnCount, matrixX.RowCount);
// The solution X has the same number of columns as B
Assert.AreEqual(matrixB.ColumnCount, matrixX.ColumnCount);
var matrixBReconstruct = matrixA * matrixX;
// Check the reconstruction.
for (var i = 0; i < matrixB.RowCount; i++)
{
for (var j = 0; j < matrixB.ColumnCount; j++)
{
AssertHelpers.AlmostEqual(matrixB[i, j], matrixBReconstruct[i, j], 10);
}
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
}
public void CanSolveForRandomVectorAndSymmetricMatrixWhenResultVectorGiven(int order)
{
var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
MatrixHelpers.ForceConjugateSymmetric(matrixA);
var matrixACopy = matrixA.Clone();
var factorEvd = matrixA.Evd();
var vectorb = MatrixLoader.GenerateRandomDenseVector(order);
var vectorbCopy = vectorb.Clone();
var resultx = new DenseVector(order);
factorEvd.Solve(vectorb, resultx);
var matrixBReconstruct = matrixA * resultx;
// Check the reconstruction.
for (var i = 0; i < vectorb.Count; i++)
{
AssertHelpers.AlmostEqual(vectorb[i], matrixBReconstruct[i], 10);
}
// Make sure A didn't change.
for (var i = 0; i < matrixA.RowCount; i++)
{
for (var j = 0; j < matrixA.ColumnCount; j++)
{
Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
}
}
// Make sure b didn't change.
for (var i = 0; i < vectorb.Count; i++)
{
Assert.AreEqual(vectorbCopy[i], vectorb[i]);
}
}
