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Fix several uninitialized member from ctor

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This commit is contained in:
Gael Guennebaud 2018-11-23 15:10:28 +01:00
parent a476054879
commit a7842daef2
9 changed files with 57 additions and 16 deletions
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2
Eigen/src/Eigenvalues/EigenSolver.h
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@ -110,7 +110,7 @@ template<typename _MatrixType> class EigenSolver
*
* \sa compute() for an example.
*/
EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false), m_realSchur(), m_matT(), m_tmp() {}
EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false), m_eigenvectorsOk(false), m_realSchur(), m_matT(), m_tmp() {}
/** \brief Default constructor with memory preallocation
*

13
Eigen/src/Eigenvalues/RealQZ.h
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@ -90,8 +90,9 @@ namespace Eigen {
m_Z(size, size),
m_workspace(size*2),
m_maxIters(400),
m_isInitialized(false)
{ }
m_isInitialized(false),
m_computeQZ(true)
{}
/** \brief Constructor; computes real QZ decomposition of given matrices
*
@ -108,9 +109,11 @@ namespace Eigen {
m_Z(A.rows(),A.cols()),
m_workspace(A.rows()*2),
m_maxIters(400),
m_isInitialized(false) {
compute(A, B, computeQZ);
}
m_isInitialized(false),
m_computeQZ(true)
{
compute(A, B, computeQZ);
}
/** \brief Returns matrix Q in the QZ decomposition.
*

9
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
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@ -122,7 +122,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
m_eivalues(),
m_subdiag(),
m_info(InvalidInput),
m_isInitialized(false)
m_isInitialized(false),
m_eigenvectorsOk(false)
{ }
/** \brief Constructor, pre-allocates memory for dynamic-size matrices.
@ -142,7 +143,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
: m_eivec(size, size),
m_eivalues(size),
m_subdiag(size > 1 ? size - 1 : 1),
m_isInitialized(false)
m_isInitialized(false),
m_eigenvectorsOk(false)
{}
/** \brief Constructor; computes eigendecomposition of given matrix.
@ -166,7 +168,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
: m_eivec(matrix.rows(), matrix.cols()),
m_eivalues(matrix.cols()),
m_subdiag(matrix.rows() > 1 ? matrix.rows() - 1 : 1),
m_isInitialized(false)
m_isInitialized(false),
m_eigenvectorsOk(false)
{
compute(matrix.derived(), options);
}

4
Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
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@ -76,12 +76,12 @@ class IncompleteCholesky : public SparseSolverBase<IncompleteCholesky<Scalar,_Up
*
* \sa IncompleteCholesky(const MatrixType&)
*/
IncompleteCholesky() : m_initialShift(1e-3),m_factorizationIsOk(false) {}
IncompleteCholesky() : m_initialShift(1e-3),m_analysisIsOk(false),m_factorizationIsOk(false) {}
/** Constructor computing the incomplete factorization for the given matrix \a matrix.
*/
template<typename MatrixType>
IncompleteCholesky(const MatrixType& matrix) : m_initialShift(1e-3),m_factorizationIsOk(false)
IncompleteCholesky(const MatrixType& matrix) : m_initialShift(1e-3),m_analysisIsOk(false),m_factorizationIsOk(false)
{
compute(matrix);
}

1
Eigen/src/PardisoSupport/PardisoSupport.h
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@ -123,6 +123,7 @@ class PardisoImpl : public SparseSolverBase<Derived>
};
PardisoImpl()
: m_analysisIsOk(false), m_factorizationIsOk(false), m_pt(0)
{
eigen_assert((sizeof(StorageIndex) >= sizeof(_INTEGER_t) && sizeof(StorageIndex) <= 8) && "Non-supported index type");
m_iparm.setZero();

26
Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
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@ -74,13 +74,35 @@ class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
};
public:
SPQR()
: m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
: m_analysisIsOk(false),
m_factorizationIsOk(false),
m_isRUpToDate(false),
m_ordering(SPQR_ORDERING_DEFAULT),
m_allow_tol(SPQR_DEFAULT_TOL),
m_tolerance (NumTraits<Scalar>::epsilon()),
m_cR(0),
m_E(0),
m_H(0),
m_HPinv(0),
m_HTau(0),
m_useDefaultThreshold(true)
{
cholmod_l_start(&m_cc);
}
explicit SPQR(const _MatrixType& matrix)
: m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
: m_analysisIsOk(false),
m_factorizationIsOk(false),
m_isRUpToDate(false),
m_ordering(SPQR_ORDERING_DEFAULT),
m_allow_tol(SPQR_DEFAULT_TOL),
m_tolerance (NumTraits<Scalar>::epsilon()),
m_cR(0),
m_E(0),
m_H(0),
m_HPinv(0),
m_HTau(0),
m_useDefaultThreshold(true)
{
cholmod_l_start(&m_cc);
compute(matrix);

2
Eigen/src/SVD/BDCSVD.h
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@ -110,7 +110,7 @@ public:
* The default constructor is useful in cases in which the user intends to
* perform decompositions via BDCSVD::compute(const MatrixType&).
*/
BDCSVD() : m_algoswap(16), m_numIters(0)
BDCSVD() : m_algoswap(16), m_isTranspose(false), m_compU(false), m_compV(false), m_numIters(0)
{}

4
Eigen/src/SVD/SVDBase.h
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@ -245,6 +245,10 @@ protected:
: m_isInitialized(false),
m_isAllocated(false),
m_usePrescribedThreshold(false),
m_computeFullU(false),
m_computeThinU(false),
m_computeFullV(false),
m_computeThinV(false),
m_computationOptions(0),
m_rows(-1), m_cols(-1), m_diagSize(0)
{

12
Eigen/src/SparseCholesky/SimplicialCholesky.h
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@ -80,11 +80,19 @@ class SimplicialCholeskyBase : public SparseSolverBase<Derived>
/** Default constructor */
SimplicialCholeskyBase()
: m_info(Success), m_shiftOffset(0), m_shiftScale(1)
: m_info(Success),
m_factorizationIsOk(false),
m_analysisIsOk(false),
m_shiftOffset(0),
m_shiftScale(1)
{}
explicit SimplicialCholeskyBase(const MatrixType& matrix)
: m_info(Success), m_shiftOffset(0), m_shiftScale(1)
: m_info(Success),
m_factorizationIsOk(false),
m_analysisIsOk(false),
m_shiftOffset(0),
m_shiftScale(1)
{
derived().compute(matrix);
}