mirror/eigen
2
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-01-18 14:34:17 +08:00
Code Issues Packages Projects Releases Wiki Activity

Test matrix functions with matrices with clustered imaginary eivals.

Browse Source 
The idea is that these test MatrixFunction::swapEntriesInSchur(),
which is not covered by existing tests. This did not work out as
expected, but nevertheless it is a good test so I left it in.
This commit is contained in:
Jitse Niesen 2010-02-13 22:49:01 +00:00
parent a4a2671fd0
commit b18f737aa1
1 changed files with 53 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

53
unsupported/test/matrix_function.cpp
View File

@ -40,6 +40,58 @@ MatrixType randomMatrixWithRealEivals(const int size)
return A.inverse() * diag * A;
}
template <typename MatrixType, int IsComplex = NumTraits<typename ei_traits<MatrixType>::Scalar>::IsComplex>
struct randomMatrixWithImagEivals
{
// Returns a matrix with eigenvalues clustered around 0 and +/- i.
static MatrixType run(const int size);
};
// Partial specialization for real matrices
template<typename MatrixType>
struct randomMatrixWithImagEivals<MatrixType, 0>
{
static MatrixType run(const int size)
{
typedef typename MatrixType::Scalar Scalar;
MatrixType diag = MatrixType::Zero(size, size);
int i = 0;
while (i < size) {
int randomInt = ei_random<int>(-1, 1);
if (randomInt == 0 || i == size-1) {
diag(i, i) = ei_random<Scalar>() * Scalar(0.01);
++i;
} else {
Scalar alpha = Scalar(randomInt) + ei_random<Scalar>() * Scalar(0.01);
diag(i, i+1) = alpha;
diag(i+1, i) = -alpha;
i += 2;
}
}
MatrixType A = MatrixType::Random(size, size);
return A.inverse() * diag * A;
}
};
// Partial specialization for complex matrices
template<typename MatrixType>
struct randomMatrixWithImagEivals<MatrixType, 1>
{
static MatrixType run(const int size)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
const Scalar imagUnit(0, 1);
MatrixType diag = MatrixType::Zero(size, size);
for (int i = 0; i < size; ++i) {
diag(i, i) = Scalar(RealScalar(ei_random<int>(-1, 1))) * imagUnit
+ ei_random<Scalar>() * Scalar(RealScalar(0.01));
}
MatrixType A = MatrixType::Random(size, size);
return A.inverse() * diag * A;
}
};
template<typename MatrixType>
void testMatrixExponential(const MatrixType& A)
{
@ -117,6 +169,7 @@ void testMatrixType(const MatrixType& m)
for (int i = 0; i < g_repeat; i++) {
testMatrix(MatrixType::Random(size, size).eval());
testMatrix(randomMatrixWithRealEivals<MatrixType>(size));
testMatrix(randomMatrixWithImagEivals<MatrixType>::run(size));
}
}