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Eigenvalues module: Implement setMaxIterations() methods.
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@ -208,27 +208,7 @@ template<typename _MatrixType> class ComplexEigenSolver
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* Example: \include ComplexEigenSolver_compute.cpp
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* Example: \include ComplexEigenSolver_compute.cpp
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* Output: \verbinclude ComplexEigenSolver_compute.out
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* Output: \verbinclude ComplexEigenSolver_compute.out
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*/
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*/
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ComplexEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true)
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ComplexEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
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{
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return computeInternal(matrix, computeEigenvectors, false, 0);
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}
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/** \brief Computes eigendecomposition with specified maximum number of iterations.
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*
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* \param[in] matrix Square matrix whose eigendecomposition is to be computed.
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* \param[in] computeEigenvectors If true, both the eigenvectors and the
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* eigenvalues are computed; if false, only the eigenvalues are
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* computed.
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* \param[in] maxIter Maximum number of iterations.
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* \returns Reference to \c *this
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*
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* This method provides the same functionality as compute(const MatrixType&, bool) but it also allows the
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* user to specify the maximum number of iterations to be used when computing the Schur decomposition.
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*/
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ComplexEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors, Index maxIter)
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{
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return computeInternal(matrix, computeEigenvectors, true, maxIter);
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}
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/** \brief Reports whether previous computation was successful.
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/** \brief Reports whether previous computation was successful.
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*
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*
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@ -240,6 +220,19 @@ template<typename _MatrixType> class ComplexEigenSolver
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return m_schur.info();
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return m_schur.info();
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}
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}
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/** \brief Sets the maximum number of iterations allowed. */
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ComplexEigenSolver& setMaxIterations(Index maxIters)
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{
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m_schur.setMaxIterations(maxIters);
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return *this;
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}
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/** \brief Returns the maximum number of iterations. */
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Index getMaxIterations()
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{
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return m_schur.getMaxIterations();
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}
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protected:
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protected:
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EigenvectorType m_eivec;
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EigenvectorType m_eivec;
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EigenvalueType m_eivalues;
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EigenvalueType m_eivalues;
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@ -251,25 +244,18 @@ template<typename _MatrixType> class ComplexEigenSolver
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private:
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private:
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void doComputeEigenvectors(RealScalar matrixnorm);
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void doComputeEigenvectors(RealScalar matrixnorm);
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void sortEigenvalues(bool computeEigenvectors);
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void sortEigenvalues(bool computeEigenvectors);
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ComplexEigenSolver& computeInternal(const MatrixType& matrix, bool computeEigenvectors,
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bool maxIterSpecified, Index maxIter);
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};
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};
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template<typename MatrixType>
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template<typename MatrixType>
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ComplexEigenSolver<MatrixType>&
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ComplexEigenSolver<MatrixType>&
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ComplexEigenSolver<MatrixType>::computeInternal(const MatrixType& matrix, bool computeEigenvectors,
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ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
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bool maxIterSpecified, Index maxIter)
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{
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{
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// this code is inspired from Jampack
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// this code is inspired from Jampack
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assert(matrix.cols() == matrix.rows());
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assert(matrix.cols() == matrix.rows());
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// Do a complex Schur decomposition, A = U T U^*
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// Do a complex Schur decomposition, A = U T U^*
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// The eigenvalues are on the diagonal of T.
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// The eigenvalues are on the diagonal of T.
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if (maxIterSpecified)
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m_schur.compute(matrix, computeEigenvectors, maxIter);
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else
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m_schur.compute(matrix, computeEigenvectors);
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m_schur.compute(matrix, computeEigenvectors);
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if(m_schur.info() == Success)
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if(m_schur.info() == Success)
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@ -96,7 +96,8 @@ template<typename _MatrixType> class ComplexSchur
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m_matU(size,size),
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m_matU(size,size),
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m_hess(size),
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m_hess(size),
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m_isInitialized(false),
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m_isInitialized(false),
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m_matUisUptodate(false)
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m_matUisUptodate(false),
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m_maxIters(-1)
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{}
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{}
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/** \brief Constructor; computes Schur decomposition of given matrix.
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/** \brief Constructor; computes Schur decomposition of given matrix.
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@ -113,7 +114,8 @@ template<typename _MatrixType> class ComplexSchur
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m_matU(matrix.rows(),matrix.cols()),
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m_matU(matrix.rows(),matrix.cols()),
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m_hess(matrix.rows()),
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m_hess(matrix.rows()),
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m_isInitialized(false),
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m_isInitialized(false),
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m_matUisUptodate(false)
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m_matUisUptodate(false),
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m_maxIters(-1)
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{
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{
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compute(matrix, computeU);
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compute(matrix, computeU);
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}
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}
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@ -184,24 +186,7 @@ template<typename _MatrixType> class ComplexSchur
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*
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*
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* \sa compute(const MatrixType&, bool, Index)
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* \sa compute(const MatrixType&, bool, Index)
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*/
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*/
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ComplexSchur& compute(const MatrixType& matrix, bool computeU = true)
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ComplexSchur& compute(const MatrixType& matrix, bool computeU = true);
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{
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return compute(matrix, computeU, m_maxIterations * matrix.rows());
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}
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/** \brief Computes Schur decomposition with specified maximum number of iterations.
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*
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* \param[in] matrix Square matrix whose Schur decomposition is to be computed.
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* \param[in] computeU If true, both T and U are computed; if false, only T is computed.
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* \param[in] maxIter Maximum number of iterations.
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*
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* \returns Reference to \c *this
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*
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* This method provides the same functionality as compute(const MatrixType&, bool) but it also allows the
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* user to specify the maximum number of QR iterations to be used. The maximum number of iterations for
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* compute(const MatrixType&, bool) is #m_maxIterations times the size of the matrix.
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*/
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ComplexSchur& compute(const MatrixType& matrix, bool computeU, Index maxIter);
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/** \brief Reports whether previous computation was successful.
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/** \brief Reports whether previous computation was successful.
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*
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*
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@ -213,12 +198,29 @@ template<typename _MatrixType> class ComplexSchur
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return m_info;
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return m_info;
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}
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}
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/** \brief Maximum number of iterations.
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/** \brief Sets the maximum number of iterations allowed.
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*
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* If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
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* of the matrix.
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*/
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ComplexSchur& setMaxIterations(Index maxIters)
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{
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m_maxIters = maxIters;
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return *this;
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}
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/** \brief Returns the maximum number of iterations. */
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Index getMaxIterations()
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{
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return m_maxIters;
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}
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/** \brief Maximum number of iterations per row.
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*
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*
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* If not otherwise specified, the maximum number of iterations is this number times the size of the
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* If not otherwise specified, the maximum number of iterations is this number times the size of the
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* matrix. It is currently set to 30.
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* matrix. It is currently set to 30.
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*/
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*/
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static const int m_maxIterations = 30;
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static const int m_maxIterationsPerRow = 30;
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protected:
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protected:
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ComplexMatrixType m_matT, m_matU;
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ComplexMatrixType m_matT, m_matU;
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@ -226,11 +228,12 @@ template<typename _MatrixType> class ComplexSchur
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ComputationInfo m_info;
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ComputationInfo m_info;
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bool m_isInitialized;
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bool m_isInitialized;
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bool m_matUisUptodate;
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bool m_matUisUptodate;
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Index m_maxIters;
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private:
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private:
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bool subdiagonalEntryIsNeglegible(Index i);
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bool subdiagonalEntryIsNeglegible(Index i);
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ComplexScalar computeShift(Index iu, Index iter);
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ComplexScalar computeShift(Index iu, Index iter);
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void reduceToTriangularForm(bool computeU, Index maxIter);
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void reduceToTriangularForm(bool computeU);
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friend struct internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>;
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friend struct internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>;
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};
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};
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@ -289,7 +292,7 @@ typename ComplexSchur<MatrixType>::ComplexScalar ComplexSchur<MatrixType>::compu
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template<typename MatrixType>
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template<typename MatrixType>
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ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU, Index maxIter)
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ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
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{
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{
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m_matUisUptodate = false;
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m_matUisUptodate = false;
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eigen_assert(matrix.cols() == matrix.rows());
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eigen_assert(matrix.cols() == matrix.rows());
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@ -305,7 +308,7 @@ ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const MatrixType& ma
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}
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}
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internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>::run(*this, matrix, computeU);
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internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>::run(*this, matrix, computeU);
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reduceToTriangularForm(computeU, maxIter);
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reduceToTriangularForm(computeU);
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return *this;
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return *this;
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}
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}
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@ -348,8 +351,12 @@ struct complex_schur_reduce_to_hessenberg<MatrixType, false>
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// Reduce the Hessenberg matrix m_matT to triangular form by QR iteration.
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// Reduce the Hessenberg matrix m_matT to triangular form by QR iteration.
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template<typename MatrixType>
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template<typename MatrixType>
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void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU, Index maxIter)
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void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
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{
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{
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Index maxIters = m_maxIters;
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if (maxIters == -1)
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maxIters = m_maxIterationsPerRow * m_matT.rows();
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// The matrix m_matT is divided in three parts.
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// The matrix m_matT is divided in three parts.
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// Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero.
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// Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero.
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// Rows il,...,iu is the part we are working on (the active submatrix).
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// Rows il,...,iu is the part we are working on (the active submatrix).
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@ -375,7 +382,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU, Index maxIt
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// if we spent too many iterations, we give up
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// if we spent too many iterations, we give up
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iter++;
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iter++;
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totalIter++;
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totalIter++;
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if(totalIter > maxIter) break;
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if(totalIter > maxIters) break;
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// find il, the top row of the active submatrix
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// find il, the top row of the active submatrix
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il = iu-1;
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il = iu-1;
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@ -405,7 +412,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU, Index maxIt
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}
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}
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}
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}
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if(totalIter <= maxIter)
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if(totalIter <= maxIters)
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m_info = Success;
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m_info = Success;
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else
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else
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m_info = NoConvergence;
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m_info = NoConvergence;
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@ -273,27 +273,7 @@ template<typename _MatrixType> class EigenSolver
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* Example: \include EigenSolver_compute.cpp
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* Example: \include EigenSolver_compute.cpp
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* Output: \verbinclude EigenSolver_compute.out
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* Output: \verbinclude EigenSolver_compute.out
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*/
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*/
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EigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true)
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EigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
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{
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return computeInternal(matrix, computeEigenvectors, false, 0);
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}
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/** \brief Computes eigendecomposition with specified maximum number of iterations.
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*
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* \param[in] matrix Square matrix whose eigendecomposition is to be computed.
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* \param[in] computeEigenvectors If true, both the eigenvectors and the
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* eigenvalues are computed; if false, only the eigenvalues are
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* computed.
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* \param[in] maxIter Maximum number of iterations.
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* \returns Reference to \c *this
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*
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* This method provides the same functionality as compute(const MatrixType&, bool) but it also allows the
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* user to specify the maximum number of iterations to be used when computing the Schur decomposition.
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*/
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EigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors, Index maxIter)
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{
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return computeInternal(matrix, computeEigenvectors, true, maxIter);
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}
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ComputationInfo info() const
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ComputationInfo info() const
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{
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{
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@ -301,10 +281,21 @@ template<typename _MatrixType> class EigenSolver
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return m_realSchur.info();
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return m_realSchur.info();
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}
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}
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/** \brief Sets the maximum number of iterations allowed. */
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EigenSolver& setMaxIterations(Index maxIters)
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{
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m_realSchur.setMaxIterations(maxIters);
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return *this;
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}
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/** \brief Returns the maximum number of iterations. */
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Index getMaxIterations()
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{
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return m_realSchur.getMaxIterations();
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}
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private:
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private:
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void doComputeEigenvectors();
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void doComputeEigenvectors();
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EigenSolver& computeInternal(const MatrixType& matrix, bool computeEigenvectors,
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bool maxIterSpecified, Index maxIter);
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protected:
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protected:
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MatrixType m_eivec;
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MatrixType m_eivec;
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@ -371,15 +362,11 @@ typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eige
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template<typename MatrixType>
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template<typename MatrixType>
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EigenSolver<MatrixType>&
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EigenSolver<MatrixType>&
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EigenSolver<MatrixType>::computeInternal(const MatrixType& matrix, bool computeEigenvectors,
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EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
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bool maxIterSpecified, Index maxIter)
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{
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{
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assert(matrix.cols() == matrix.rows());
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assert(matrix.cols() == matrix.rows());
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// Reduce to real Schur form.
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// Reduce to real Schur form.
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if (maxIterSpecified)
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m_realSchur.compute(matrix, computeEigenvectors, maxIter);
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else
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m_realSchur.compute(matrix, computeEigenvectors);
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m_realSchur.compute(matrix, computeEigenvectors);
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if (m_realSchur.info() == Success)
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if (m_realSchur.info() == Success)
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@ -86,7 +86,8 @@ template<typename _MatrixType> class RealSchur
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m_workspaceVector(size),
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m_workspaceVector(size),
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m_hess(size),
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m_hess(size),
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m_isInitialized(false),
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m_isInitialized(false),
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m_matUisUptodate(false)
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m_matUisUptodate(false),
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m_maxIters(-1)
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{ }
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{ }
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/** \brief Constructor; computes real Schur decomposition of given matrix.
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/** \brief Constructor; computes real Schur decomposition of given matrix.
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@ -105,7 +106,8 @@ template<typename _MatrixType> class RealSchur
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m_workspaceVector(matrix.rows()),
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m_workspaceVector(matrix.rows()),
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m_hess(matrix.rows()),
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m_hess(matrix.rows()),
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m_isInitialized(false),
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m_isInitialized(false),
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m_matUisUptodate(false)
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m_matUisUptodate(false),
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m_maxIters(-1)
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{
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{
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compute(matrix, computeU);
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compute(matrix, computeU);
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}
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}
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@ -163,24 +165,7 @@ template<typename _MatrixType> class RealSchur
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*
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*
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* \sa compute(const MatrixType&, bool, Index)
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* \sa compute(const MatrixType&, bool, Index)
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*/
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*/
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RealSchur& compute(const MatrixType& matrix, bool computeU = true)
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RealSchur& compute(const MatrixType& matrix, bool computeU = true);
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{
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return compute(matrix, computeU, m_maxIterations * matrix.rows());
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}
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/** \brief Computes Schur decomposition with specified maximum number of iterations.
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*
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* \param[in] matrix Square matrix whose Schur decomposition is to be computed.
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* \param[in] computeU If true, both T and U are computed; if false, only T is computed.
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* \param[in] maxIter Maximum number of iterations.
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*
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* \returns Reference to \c *this
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*
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* This method provides the same functionality as compute(const MatrixType&, bool) but it also allows the
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* user to specify the maximum number of QR iterations to be used. The maximum number of iterations for
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* compute(const MatrixType&, bool) is #m_maxIterations times the size of the matrix.
|
|
||||||
*/
|
|
||||||
RealSchur& compute(const MatrixType& matrix, bool computeU, Index maxIter);
|
|
||||||
|
|
||||||
/** \brief Reports whether previous computation was successful.
|
/** \brief Reports whether previous computation was successful.
|
||||||
*
|
*
|
||||||
@ -192,12 +177,29 @@ template<typename _MatrixType> class RealSchur
|
|||||||
return m_info;
|
return m_info;
|
||||||
}
|
}
|
||||||
|
|
||||||
/** \brief Maximum number of iterations.
|
/** \brief Sets the maximum number of iterations allowed.
|
||||||
|
*
|
||||||
|
* If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
|
||||||
|
* of the matrix.
|
||||||
|
*/
|
||||||
|
RealSchur& setMaxIterations(Index maxIters)
|
||||||
|
{
|
||||||
|
m_maxIters = maxIters;
|
||||||
|
return *this;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** \brief Returns the maximum number of iterations. */
|
||||||
|
Index getMaxIterations()
|
||||||
|
{
|
||||||
|
return m_maxIters;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** \brief Maximum number of iterations per row.
|
||||||
*
|
*
|
||||||
* If not otherwise specified, the maximum number of iterations is this number times the size of the
|
* If not otherwise specified, the maximum number of iterations is this number times the size of the
|
||||||
* matrix. It is currently set to 40.
|
* matrix. It is currently set to 40.
|
||||||
*/
|
*/
|
||||||
static const int m_maxIterations = 40;
|
static const int m_maxIterationsPerRow = 40;
|
||||||
|
|
||||||
private:
|
private:
|
||||||
|
|
||||||
@ -208,6 +210,7 @@ template<typename _MatrixType> class RealSchur
|
|||||||
ComputationInfo m_info;
|
ComputationInfo m_info;
|
||||||
bool m_isInitialized;
|
bool m_isInitialized;
|
||||||
bool m_matUisUptodate;
|
bool m_matUisUptodate;
|
||||||
|
Index m_maxIters;
|
||||||
|
|
||||||
typedef Matrix<Scalar,3,1> Vector3s;
|
typedef Matrix<Scalar,3,1> Vector3s;
|
||||||
|
|
||||||
@ -221,9 +224,12 @@ template<typename _MatrixType> class RealSchur
|
|||||||
|
|
||||||
|
|
||||||
template<typename MatrixType>
|
template<typename MatrixType>
|
||||||
RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU, Index maxIter)
|
RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
|
||||||
{
|
{
|
||||||
assert(matrix.cols() == matrix.rows());
|
assert(matrix.cols() == matrix.rows());
|
||||||
|
Index maxIters = m_maxIters;
|
||||||
|
if (maxIters == -1)
|
||||||
|
maxIters = m_maxIterationsPerRow * matrix.rows();
|
||||||
|
|
||||||
// Step 1. Reduce to Hessenberg form
|
// Step 1. Reduce to Hessenberg form
|
||||||
m_hess.compute(matrix);
|
m_hess.compute(matrix);
|
||||||
@ -273,14 +279,14 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
|
|||||||
computeShift(iu, iter, exshift, shiftInfo);
|
computeShift(iu, iter, exshift, shiftInfo);
|
||||||
iter = iter + 1;
|
iter = iter + 1;
|
||||||
totalIter = totalIter + 1;
|
totalIter = totalIter + 1;
|
||||||
if (totalIter > maxIter) break;
|
if (totalIter > maxIters) break;
|
||||||
Index im;
|
Index im;
|
||||||
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
|
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
|
||||||
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
|
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
if(totalIter <= maxIter)
|
if(totalIter <= maxIters)
|
||||||
m_info = Success;
|
m_info = Success;
|
||||||
else
|
else
|
||||||
m_info = NoConvergence;
|
m_info = NoConvergence;
|
||||||
|
@ -60,13 +60,14 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
|
|||||||
verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
|
verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
|
||||||
|
|
||||||
ComplexEigenSolver<MatrixType> ei2;
|
ComplexEigenSolver<MatrixType> ei2;
|
||||||
ei2.compute(a, true, ComplexSchur<MatrixType>::m_maxIterations * rows);
|
ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
|
||||||
VERIFY_IS_EQUAL(ei2.info(), Success);
|
VERIFY_IS_EQUAL(ei2.info(), Success);
|
||||||
VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
|
VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
|
||||||
VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
|
VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
|
||||||
if (rows > 2) {
|
if (rows > 2) {
|
||||||
ei2.compute(a, true, 1);
|
ei2.setMaxIterations(1).compute(a);
|
||||||
VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
|
VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
|
||||||
|
VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
|
||||||
}
|
}
|
||||||
|
|
||||||
ComplexEigenSolver<MatrixType> eiNoEivecs(a, false);
|
ComplexEigenSolver<MatrixType> eiNoEivecs(a, false);
|
||||||
|
@ -46,13 +46,14 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
|
|||||||
VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
|
VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
|
||||||
|
|
||||||
EigenSolver<MatrixType> ei2;
|
EigenSolver<MatrixType> ei2;
|
||||||
ei2.compute(a, true, RealSchur<MatrixType>::m_maxIterations * rows);
|
ei2.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
|
||||||
VERIFY_IS_EQUAL(ei2.info(), Success);
|
VERIFY_IS_EQUAL(ei2.info(), Success);
|
||||||
VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
|
VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
|
||||||
VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
|
VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
|
||||||
if (rows > 2) {
|
if (rows > 2) {
|
||||||
ei2.compute(a, true, 1);
|
ei2.setMaxIterations(1).compute(a);
|
||||||
VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
|
VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
|
||||||
|
VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
|
||||||
}
|
}
|
||||||
|
|
||||||
EigenSolver<MatrixType> eiNoEivecs(a, false);
|
EigenSolver<MatrixType> eiNoEivecs(a, false);
|
||||||
|
@ -49,16 +49,17 @@ template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTim
|
|||||||
|
|
||||||
// Test maximum number of iterations
|
// Test maximum number of iterations
|
||||||
ComplexSchur<MatrixType> cs3;
|
ComplexSchur<MatrixType> cs3;
|
||||||
cs3.compute(A, true, ComplexSchur<MatrixType>::m_maxIterations * size);
|
cs3.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * size).compute(A);
|
||||||
VERIFY_IS_EQUAL(cs3.info(), Success);
|
VERIFY_IS_EQUAL(cs3.info(), Success);
|
||||||
VERIFY_IS_EQUAL(cs3.matrixT(), cs1.matrixT());
|
VERIFY_IS_EQUAL(cs3.matrixT(), cs1.matrixT());
|
||||||
VERIFY_IS_EQUAL(cs3.matrixU(), cs1.matrixU());
|
VERIFY_IS_EQUAL(cs3.matrixU(), cs1.matrixU());
|
||||||
cs3.compute(A, true, 1);
|
cs3.setMaxIterations(1).compute(A);
|
||||||
VERIFY_IS_EQUAL(cs3.info(), size > 1 ? NoConvergence : Success);
|
VERIFY_IS_EQUAL(cs3.info(), size > 1 ? NoConvergence : Success);
|
||||||
|
VERIFY_IS_EQUAL(cs3.getMaxIterations(), 1);
|
||||||
|
|
||||||
MatrixType Atriangular = A;
|
MatrixType Atriangular = A;
|
||||||
Atriangular.template triangularView<StrictlyLower>().setZero();
|
Atriangular.template triangularView<StrictlyLower>().setZero();
|
||||||
cs3.compute(Atriangular, true, 1); // triangular matrices do not need any iterations
|
cs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations
|
||||||
VERIFY_IS_EQUAL(cs3.info(), Success);
|
VERIFY_IS_EQUAL(cs3.info(), Success);
|
||||||
VERIFY_IS_EQUAL(cs3.matrixT(), Atriangular.template cast<ComplexScalar>());
|
VERIFY_IS_EQUAL(cs3.matrixT(), Atriangular.template cast<ComplexScalar>());
|
||||||
VERIFY_IS_EQUAL(cs3.matrixU(), ComplexMatrixType::Identity(size, size));
|
VERIFY_IS_EQUAL(cs3.matrixU(), ComplexMatrixType::Identity(size, size));
|
||||||
|
@ -68,18 +68,19 @@ template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTim
|
|||||||
|
|
||||||
// Test maximum number of iterations
|
// Test maximum number of iterations
|
||||||
RealSchur<MatrixType> rs3;
|
RealSchur<MatrixType> rs3;
|
||||||
rs3.compute(A, true, RealSchur<MatrixType>::m_maxIterations * size);
|
rs3.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * size).compute(A);
|
||||||
VERIFY_IS_EQUAL(rs3.info(), Success);
|
VERIFY_IS_EQUAL(rs3.info(), Success);
|
||||||
VERIFY_IS_EQUAL(rs3.matrixT(), rs1.matrixT());
|
VERIFY_IS_EQUAL(rs3.matrixT(), rs1.matrixT());
|
||||||
VERIFY_IS_EQUAL(rs3.matrixU(), rs1.matrixU());
|
VERIFY_IS_EQUAL(rs3.matrixU(), rs1.matrixU());
|
||||||
if (size > 2) {
|
if (size > 2) {
|
||||||
rs3.compute(A, true, 1);
|
rs3.setMaxIterations(1).compute(A);
|
||||||
VERIFY_IS_EQUAL(rs3.info(), NoConvergence);
|
VERIFY_IS_EQUAL(rs3.info(), NoConvergence);
|
||||||
|
VERIFY_IS_EQUAL(rs3.getMaxIterations(), 1);
|
||||||
}
|
}
|
||||||
|
|
||||||
MatrixType Atriangular = A;
|
MatrixType Atriangular = A;
|
||||||
Atriangular.template triangularView<StrictlyLower>().setZero();
|
Atriangular.template triangularView<StrictlyLower>().setZero();
|
||||||
rs3.compute(Atriangular, true, 1); // triangular matrices do not need any iterations
|
rs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations
|
||||||
VERIFY_IS_EQUAL(rs3.info(), Success);
|
VERIFY_IS_EQUAL(rs3.info(), Success);
|
||||||
VERIFY_IS_EQUAL(rs3.matrixT(), Atriangular);
|
VERIFY_IS_EQUAL(rs3.matrixT(), Atriangular);
|
||||||
VERIFY_IS_EQUAL(rs3.matrixU(), MatrixType::Identity(size, size));
|
VERIFY_IS_EQUAL(rs3.matrixU(), MatrixType::Identity(size, size));
|
||||||
|
Loading…
x
Reference in New Issue
Block a user