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https://gitlab.com/libeigen/eigen.git
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Fix most Doxygen warnings. Also add links to stable documentation from unsupported modules (by using the corresponding Doxytags file).
Manually grafted from d107a371c6
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@@ -21,7 +21,7 @@ namespace internal {
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*
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* Parameters:
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* \param mat matrix of linear system of equations
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* \param Rhs right hand side vector of linear system of equations
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* \param rhs right hand side vector of linear system of equations
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* \param x on input: initial guess, on output: solution
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* \param precond preconditioner used
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* \param iters on input: maximum number of iterations to perform
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@@ -7,8 +7,8 @@
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_MATRIX_FUNCTION
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#define EIGEN_MATRIX_FUNCTION
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#ifndef EIGEN_MATRIX_FUNCTION_H
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#define EIGEN_MATRIX_FUNCTION_H
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#include "StemFunction.h"
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@@ -566,4 +566,4 @@ const MatrixFunctionReturnValue<Derived> MatrixBase<Derived>::cosh() const
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} // end namespace Eigen
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#endif // EIGEN_MATRIX_FUNCTION
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#endif // EIGEN_MATRIX_FUNCTION_H
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@@ -324,7 +324,7 @@ public:
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/** \brief Compute the matrix logarithm.
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*
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* \param[out] result Logarithm of \p A, where \A is as specified in the constructor.
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* \param[out] result Logarithm of \c A, where \c A is as specified in the constructor.
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*/
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template <typename ResultType>
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inline void evalTo(ResultType& result) const
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@@ -56,8 +56,8 @@ class MatrixPowerParenthesesReturnValue : public ReturnByValue< MatrixPowerParen
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* \param[out] result
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*/
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template<typename ResultType>
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inline void evalTo(ResultType& res) const
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{ m_pow.compute(res, m_p); }
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inline void evalTo(ResultType& result) const
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{ m_pow.compute(result, m_p); }
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Index rows() const { return m_pow.rows(); }
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Index cols() const { return m_pow.cols(); }
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@@ -614,8 +614,8 @@ class MatrixPowerReturnValue : public ReturnByValue< MatrixPowerReturnValue<Deri
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* constructor.
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*/
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template<typename ResultType>
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inline void evalTo(ResultType& res) const
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{ MatrixPower<PlainObject>(m_A.eval()).compute(res, m_p); }
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inline void evalTo(ResultType& result) const
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{ MatrixPower<PlainObject>(m_A.eval()).compute(result, m_p); }
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Index rows() const { return m_A.rows(); }
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Index cols() const { return m_A.cols(); }
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@@ -664,8 +664,8 @@ class MatrixComplexPowerReturnValue : public ReturnByValue< MatrixComplexPowerRe
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* constructor.
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*/
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template<typename ResultType>
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inline void evalTo(ResultType& res) const
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{ res = (m_p * m_A.log()).exp(); }
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inline void evalTo(ResultType& result) const
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{ result = (m_p * m_A.log()).exp(); }
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Index rows() const { return m_A.rows(); }
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Index cols() const { return m_A.cols(); }
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@@ -20,8 +20,8 @@ namespace Eigen {
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* e.g. \f$ 1 + 3x^2 \f$ is stored as a vector \f$ [ 1, 0, 3 ] \f$.
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* \param[in] x : the value to evaluate the polynomial at.
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*
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* <i><b>Note for stability:</b></i>
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* <dd> \f$ |x| \le 1 \f$ </dd>
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* \note for stability:
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* \f$ |x| \le 1 \f$
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*/
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template <typename Polynomials, typename T>
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inline
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@@ -67,8 +67,8 @@ T poly_eval( const Polynomials& poly, const T& x )
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* by degrees i.e. poly[i] is the coefficient of degree i of the polynomial
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* e.g. \f$ 1 + 3x^2 \f$ is stored as a vector \f$ [ 1, 0, 3 ] \f$.
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*
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* <i><b>Precondition:</b></i>
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* <dd> the leading coefficient of the input polynomial poly must be non zero </dd>
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* \pre
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* the leading coefficient of the input polynomial poly must be non zero
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*/
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template <typename Polynomial>
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inline
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@@ -931,7 +931,7 @@ class BlockSparseMatrix : public SparseMatrixBase<BlockSparseMatrix<_Scalar,_Blo
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}
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/**
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* \returns the starting position of the block <id> in the array of values
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* \returns the starting position of the block \p id in the array of values
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*/
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Index blockPtr(Index id) const
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{
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