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Use matrices with clustered eigenvalues in matrix function test.

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This is in order to get better code coverage.
Test matrix_function_3 now fails regularly because ComplexSchur
reaches the max number of iterations; further study needed.
This commit is contained in:
Jitse Niesen 2010-01-24 22:56:28 +00:00
parent d08035f3e1
commit 858539a6af
1 changed files with 32 additions and 17 deletions
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49
unsupported/test/matrix_function.cpp
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@ -25,18 +25,37 @@
#include "main.h"
#include <unsupported/Eigen/MatrixFunctions>
// Returns either a matrix with iid random entries or a matrix with
// clustered eigenvalues. Matrices with clustered eigenvalue clusters
// lead to different code paths in MatrixFunction.h and are thus
// useful for testing.
template<typename MatrixType>
void testMatrixExponential(const MatrixType& m)
MatrixType createRandomMatrix(const int size)
{
typedef typename MatrixType::Scalar Scalar;
MatrixType result;
if (ei_random<int>(0,1) == 0) {
result = MatrixType::Random(size, size);
} else {
MatrixType diag = MatrixType::Zero(size, size);
for (int i = 0; i < size; ++i) {
diag(i, i) = static_cast<Scalar>(ei_random<int>(0,2))
+ ei_random<Scalar>() * static_cast<Scalar>(0.01);
}
MatrixType A = MatrixType::Random(size, size);
result = A.inverse() * diag * A;
}
return result;
}
template<typename MatrixType>
void testMatrixExponential(const MatrixType& A)
{
typedef typename ei_traits<MatrixType>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef std::complex<RealScalar> ComplexScalar;
const int rows = m.rows();
const int cols = m.cols();
for (int i = 0; i < g_repeat; i++) {
MatrixType A = MatrixType::Random(rows, cols);
MatrixType expA1, expA2;
ei_matrix_exponential(A, &expA1);
ei_matrix_function(A, StdStemFunctions<ComplexScalar>::exp, &expA2);
@ -45,13 +64,9 @@ void testMatrixExponential(const MatrixType& m)
}
template<typename MatrixType>
void testHyperbolicFunctions(const MatrixType& m)
void testHyperbolicFunctions(const MatrixType& A)
{
const int rows = m.rows();
const int cols = m.cols();
for (int i = 0; i < g_repeat; i++) {
MatrixType A = MatrixType::Random(rows, cols);
MatrixType sinhA, coshA, expA;
ei_matrix_sinh(A, &sinhA);
ei_matrix_cosh(A, &coshA);
@ -62,7 +77,7 @@ void testHyperbolicFunctions(const MatrixType& m)
}
template<typename MatrixType>
void testGonioFunctions(const MatrixType& m)
void testGonioFunctions(const MatrixType& A)
{
typedef ei_traits<MatrixType> Traits;
typedef typename Traits::Scalar Scalar;
@ -71,13 +86,10 @@ void testGonioFunctions(const MatrixType& m)
typedef Matrix<ComplexScalar, Traits::RowsAtCompileTime,
Traits::ColsAtCompileTime, MatrixType::Options> ComplexMatrix;
const int rows = m.rows();
const int cols = m.cols();
ComplexScalar imagUnit(0,1);
ComplexScalar two(2,0);
for (int i = 0; i < g_repeat; i++) {
MatrixType A = MatrixType::Random(rows, cols);
ComplexMatrix Ac = A.template cast<ComplexScalar>();
ComplexMatrix exp_iA;
@ -98,9 +110,12 @@ void testGonioFunctions(const MatrixType& m)
template<typename MatrixType>
void testMatrixType(const MatrixType& m)
{
testMatrixExponential(m);
testHyperbolicFunctions(m);
testGonioFunctions(m);
for (int i = 0; i < g_repeat; i++) {
MatrixType A = createRandomMatrix<MatrixType>(m.rows());
testMatrixExponential(A);
testHyperbolicFunctions(A);
testGonioFunctions(A);
}
}
void test_matrix_function()