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Finally fixed the matrix function/exponential warning.

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Index fixes.
This commit is contained in:
Hauke Heibel 2010-06-20 23:13:24 +02:00
parent 69b50047d6
commit bb46a45340
4 changed files with 19 additions and 15 deletions
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3
test/nullary.cpp
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@ -49,11 +49,12 @@ bool equalsIdentity(const MatrixType& A)
template<typename VectorType>
void testVectorType(const VectorType& base)
{
typedef typename ei_traits<VectorType>::Index Index;
typedef typename ei_traits<VectorType>::Scalar Scalar;
Scalar low = ei_random<Scalar>(-500,500);
Scalar high = ei_random<Scalar>(-500,500);
if (low>high) std::swap(low,high);
const int size = base.size();
const Index size = base.size();
const Scalar step = (high-low)/(size-1);
// check whether the result yields what we expect it to do

2
unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
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@ -132,7 +132,7 @@ class MatrixExponential {
typedef typename NumTraits<Scalar>::Real RealScalar;
/** \brief Reference to matrix whose exponential is to be computed. */
const typename ei_nested<MatrixType>::type m_M;
typename ei_nested<MatrixType>::type m_M;
/** \brief Even-degree terms in numerator of Pad&eacute; approximant. */
MatrixType m_U;

6
unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
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@ -117,7 +117,7 @@ class MatrixFunction<MatrixType, 0>
}
private:
const typename ei_nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
typename ei_nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
StemFunction *m_f; /**< \brief Stem function for matrix function under consideration */
MatrixFunction& operator=(const MatrixFunction&);
@ -167,7 +167,7 @@ class MatrixFunction<MatrixType, 1>
void computeOffDiagonal();
DynMatrixType solveTriangularSylvester(const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C);
const typename ei_nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
typename ei_nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
StemFunction *m_f; /**< \brief Stem function for matrix function under consideration */
MatrixType m_T; /**< \brief Triangular part of Schur decomposition */
MatrixType m_U; /**< \brief Unitary part of Schur decomposition */
@ -529,7 +529,7 @@ template<typename Derived> class MatrixFunctionReturnValue
Index cols() const { return m_A.cols(); }
private:
const typename ei_nested<Derived>::type m_A;
typename ei_nested<Derived>::type m_A;
StemFunction *m_f;
MatrixFunctionReturnValue& operator=(const MatrixFunctionReturnValue&);

23
unsupported/test/matrix_function.cpp
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@ -38,12 +38,13 @@ inline bool test_isApprox_abs(const Type1& a, const Type2& b)
// Returns a matrix with eigenvalues clustered around 0, 1 and 2.
template<typename MatrixType>
MatrixType randomMatrixWithRealEivals(const int size)
MatrixType randomMatrixWithRealEivals(const typename MatrixType::Index size)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
MatrixType diag = MatrixType::Zero(size, size);
for (int i = 0; i < size; ++i) {
for (Index i = 0; i < size; ++i) {
diag(i, i) = Scalar(RealScalar(ei_random<int>(0,2)))
+ ei_random<Scalar>() * Scalar(RealScalar(0.01));
}
@ -56,20 +57,21 @@ template <typename MatrixType, int IsComplex = NumTraits<typename ei_traits<Matr
struct randomMatrixWithImagEivals
{
// Returns a matrix with eigenvalues clustered around 0 and +/- i.
static MatrixType run(const int size);
static MatrixType run(const typename MatrixType::Index size);
};
// Partial specialization for real matrices
template<typename MatrixType>
struct randomMatrixWithImagEivals<MatrixType, 0>
{
static MatrixType run(const int size)
static MatrixType run(const typename MatrixType::Index size)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
MatrixType diag = MatrixType::Zero(size, size);
int i = 0;
Index i = 0;
while (i < size) {
int randomInt = ei_random<int>(-1, 1);
Index randomInt = ei_random<Index>(-1, 1);
if (randomInt == 0 || i == size-1) {
diag(i, i) = ei_random<Scalar>() * Scalar(0.01);
++i;
@ -90,14 +92,14 @@ struct randomMatrixWithImagEivals<MatrixType, 0>
template<typename MatrixType>
struct randomMatrixWithImagEivals<MatrixType, 1>
{
static MatrixType run(const int size)
static MatrixType run(const typename MatrixType::Index 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
for (Index i = 0; i < size; ++i) {
diag(i, i) = Scalar(RealScalar(ei_random<Index>(-1, 1))) * imagUnit
+ ei_random<Scalar>() * Scalar(RealScalar(0.01));
}
MatrixType A = MatrixType::Random(size, size);
@ -163,8 +165,9 @@ void testMatrixType(const MatrixType& m)
{
// Matrices with clustered eigenvalue lead to different code paths
// in MatrixFunction.h and are thus useful for testing.
typedef typename MatrixType::Index Index;
const int size = m.rows();
const Index size = m.rows();
for (int i = 0; i < g_repeat; i++) {
testMatrix(MatrixType::Random(size, size).eval());
testMatrix(randomMatrixWithRealEivals<MatrixType>(size));