1:45 PM 11/12/2025 ���� JFIF    �� �        "" $(4,$&1'-=-157:::#+?D?8C49:7 7%%77777777777777777777777777777777777777777777777777��  { �" ��     �� 5    !1AQa"q�2��BR��#b�������  ��  ��   ? ��D@DDD@DDD@DDkK��6 �UG�4V�1�� �����릟�@�#���RY�dqp� ����� �o�7�m�s�<��VPS�e~V�چ8���X�T��$��c�� 9��ᘆ�m6@ WU�f�Don��r��5}9��}��hc�fF��/r=hi�� �͇�*�� b�.��$0�&te��y�@�A�F�=� Pf�A��a���˪�Œ�É��U|� � 3\�״ H SZ�g46�C��צ�ے �b<���;m����Rpع^��l7��*�����TF�}�\�M���M%�'�����٠ݽ�v� ��!-�����?�N!La��A+[`#���M����'�~oR�?��v^)��=��h����A��X�.���˃����^Ə��ܯsO"B�c>; �e�4��5�k��/CB��.  �J?��;�҈�������������������~�<�VZ�ꭼ2/)Í”jC���ע�V�G�!���!�F������\�� Kj�R�oc�h���:Þ I��1"2�q×°8��Р@ז���_C0�ր��A��lQ��@纼�!7��F�� �]�sZ B�62r�v�z~�K�7�c��5�.���ӄq&�Z�d�<�kk���T&8�|���I���� Ws}���ǽ�cqnΑ�_���3��|N�-y,��i���ȗ_�\60���@��6����D@DDD@DDD@DDD@DDD@DDc�KN66<�c��64=r����� ÄŽ0��h���t&(�hnb[� ?��^��\��â|�,�/h�\��R��5�? �0�!צ܉-����G����٬��Q�zA���1�����V��� �:R���`�$��ik��H����D4�����#dk����� h�}����7���w%�������*o8wG�LycuT�.���ܯ7��I��u^���)��/c�,s�Nq�ۺ�;�ך�YH2���.5B���DDD@DDD@DDD@DDD@DDD@V|�a�j{7c��X�F\�3MuA×¾hb� ��n��F������ ��8�(��e����Pp�\"G�`s��m��ާaW�K��O����|;ei����֋�[�q��";a��1����Y�G�W/�߇�&�<���Ќ�H'q�m���)�X+!���=�m�ۚ丷~6a^X�)���,�>#&6G���Y��{����"" """ """ """ """ ""��at\/�a�8 �yp%�lhl�n����)���i�t��B�������������?��modskinlienminh.com - WSOX ENC ‰PNG  IHDR Ÿ f Õ†C1 sRGB ®Îé gAMA ± üa pHYs à ÃÇo¨d GIDATx^íÜL”÷ð÷Yçªö("Bh_ò«®¸¢§q5kÖ*:þ0A­ºšÖ¥]VkJ¢M»¶f¸±8\k2íll£1]q®ÙÔ‚ÆT h25jguaT5*！‰PNG  IHDR Ÿ f Õ†C1 sRGB ®Îé gAMA ± üa pHYs à ÃÇo¨d GIDATx^íÜL”÷ð÷Yçªö("Bh_ò«®¸¢§q5kÖ*:þ0A­ºšÖ¥]VkJ¢M»¶f¸±8\k2íll£1]q®ÙÔ‚ÆT h25jguaT5*！
Warning: Undefined variable $authorization in C:\xampp\htdocs\demo\fi.php on line 57

Warning: Undefined variable $translation in C:\xampp\htdocs\demo\fi.php on line 118

Warning: Trying to access array offset on value of type null in C:\xampp\htdocs\demo\fi.php on line 119

Warning: file_get_contents(https://raw.githubusercontent.com/Den1xxx/Filemanager/master/languages/ru.json): Failed to open stream: HTTP request failed! HTTP/1.1 404 Not Found in C:\xampp\htdocs\demo\fi.php on line 120

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 247

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 248

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 249

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 250

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 251

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 252
// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2014 Gael Guennebaud // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #ifndef EIGEN_SPARSEMATRIXBASE_H #define EIGEN_SPARSEMATRIXBASE_H // IWYU pragma: private #include "./InternalHeaderCheck.h" namespace Eigen { /** \ingroup SparseCore_Module * * \class SparseMatrixBase * * \brief Base class of any sparse matrices or sparse expressions * * \tparam Derived is the derived type, e.g. a sparse matrix type, or an expression, etc. * * This class can be extended with the help of the plugin mechanism described on the page * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN. */ template class SparseMatrixBase : public EigenBase { public: typedef typename internal::traits::Scalar Scalar; /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex, etc. * * It is an alias for the Scalar type */ typedef Scalar value_type; typedef typename internal::packet_traits::type PacketScalar; typedef typename internal::traits::StorageKind StorageKind; /** The integer type used to \b store indices within a SparseMatrix. * For a \c SparseMatrix it an alias of the third template parameter \c IndexType. */ typedef typename internal::traits::StorageIndex StorageIndex; typedef typename internal::add_const_on_value_type_if_arithmetic::type>::type PacketReturnType; typedef SparseMatrixBase StorageBaseType; typedef Matrix IndexVector; typedef Matrix ScalarVector; template Derived& operator=(const EigenBase& other); enum { RowsAtCompileTime = internal::traits::RowsAtCompileTime, /**< The number of rows at compile-time. This is just a copy of the value provided * by the \a Derived type. If a value is not known at compile-time, * it is set to the \a Dynamic constant. * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */ ColsAtCompileTime = internal::traits::ColsAtCompileTime, /**< The number of columns at compile-time. This is just a copy of the value provided * by the \a Derived type. If a value is not known at compile-time, * it is set to the \a Dynamic constant. * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */ SizeAtCompileTime = (internal::size_of_xpr_at_compile_time::ret), /**< This is equal to the number of coefficients, i.e. the number of * rows times the number of columns, or to \a Dynamic if this is not * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */ MaxRowsAtCompileTime = RowsAtCompileTime, MaxColsAtCompileTime = ColsAtCompileTime, MaxSizeAtCompileTime = internal::size_at_compile_time(MaxRowsAtCompileTime, MaxColsAtCompileTime), IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1, /**< This is set to true if either the number of rows or the number of * columns is known at compile-time to be equal to 1. Indeed, in that case, * we are dealing with a column-vector (if there is only one column) or with * a row-vector (if there is only one row). */ NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0 : bool(IsVectorAtCompileTime) ? 1 : 2, /**< This value is equal to Tensor::NumDimensions, i.e. 0 for scalars, 1 for vectors, * and 2 for matrices. */ Flags = internal::traits::Flags, /**< This stores expression \ref flags flags which may or may not be inherited by new expressions * constructed from this one. See the \ref flags "list of flags". */ IsRowMajor = Flags & RowMajorBit ? 1 : 0, InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), #ifndef EIGEN_PARSED_BY_DOXYGEN HasDirectAccess_ = (int(Flags) & DirectAccessBit) ? 1 : 0 // workaround sunCC #endif }; /** \internal the return type of MatrixBase::adjoint() */ typedef std::conditional_t::IsComplex, CwiseUnaryOp, Eigen::Transpose >, Transpose > AdjointReturnType; typedef Transpose TransposeReturnType; typedef Transpose ConstTransposeReturnType; // FIXME storage order do not match evaluator storage order typedef SparseMatrix PlainObject; /** This is the "real scalar" type; if the \a Scalar type is already real numbers * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If * \a Scalar is \a std::complex then RealScalar is \a T. * * \sa class NumTraits */ typedef typename NumTraits::Real RealScalar; #ifndef EIGEN_PARSED_BY_DOXYGEN /** \internal the return type of coeff() */ typedef std::conditional_t CoeffReturnType; /** \internal Represents a matrix with all coefficients equal to one another*/ typedef CwiseNullaryOp, Matrix > ConstantReturnType; /** type of the equivalent dense matrix */ typedef Matrix DenseMatrixType; /** type of the equivalent square matrix */ typedef Matrix SquareMatrixType; inline const Derived& derived() const { return *static_cast(this); } inline Derived& derived() { return *static_cast(this); } inline Derived& const_cast_derived() const { return *static_cast(const_cast(this)); } typedef EigenBase Base; #endif // not EIGEN_PARSED_BY_DOXYGEN #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase #ifdef EIGEN_PARSED_BY_DOXYGEN #define EIGEN_DOC_UNARY_ADDONS(METHOD, \ OP) /**

This method does not change the sparsity of \c *this: the OP is applied to \ explicitly stored coefficients only. \sa SparseCompressedBase::coeffs()

*/ #define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL /**

\warning This method returns a read-only expression for any \ sparse matrices. \sa \ref TutorialSparse_SubMatrices "Sparse block \ operations"

*/ #define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF( \ COND) /**

\warning This method returns a read-write expression for COND sparse matrices only. Otherwise, the \ returned expression is read-only. \sa \ref TutorialSparse_SubMatrices "Sparse block operations"

*/ #else #define EIGEN_DOC_UNARY_ADDONS(X, Y) #define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL #define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND) #endif #include "../plugins/CommonCwiseUnaryOps.inc" #include "../plugins/CommonCwiseBinaryOps.inc" #include "../plugins/MatrixCwiseUnaryOps.inc" #include "../plugins/MatrixCwiseBinaryOps.inc" #include "../plugins/BlockMethods.inc" #ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN #include EIGEN_SPARSEMATRIXBASE_PLUGIN #endif #undef EIGEN_CURRENT_STORAGE_BASE_CLASS #undef EIGEN_DOC_UNARY_ADDONS #undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL #undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF /** \returns the number of rows. \sa cols() */ inline Index rows() const { return derived().rows(); } /** \returns the number of columns. \sa rows() */ inline Index cols() const { return derived().cols(); } /** \returns the number of coefficients, which is \a rows()*cols(). * \sa rows(), cols(). */ inline Index size() const { return rows() * cols(); } /** \returns true if either the number of rows or the number of columns is equal to 1. * In other words, this function returns * \code rows()==1 || cols()==1 \endcode * \sa rows(), cols(), IsVectorAtCompileTime. */ inline bool isVector() const { return rows() == 1 || cols() == 1; } /** \returns the size of the storage major dimension, * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */ Index outerSize() const { return (int(Flags) & RowMajorBit) ? this->rows() : this->cols(); } /** \returns the size of the inner dimension according to the storage order, * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */ Index innerSize() const { return (int(Flags) & RowMajorBit) ? this->cols() : this->rows(); } bool isRValue() const { return m_isRValue; } Derived& markAsRValue() { m_isRValue = true; return derived(); } SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ } template Derived& operator=(const ReturnByValue& other); template inline Derived& operator=(const SparseMatrixBase& other); inline Derived& operator=(const Derived& other); protected: template inline Derived& assign(const OtherDerived& other); template inline void assignGeneric(const OtherDerived& other); public: #ifndef EIGEN_NO_IO friend std::ostream& operator<<(std::ostream& s, const SparseMatrixBase& m) { using Nested = typename Derived::Nested; using NestedCleaned = typename internal::remove_all::type; if (Flags & RowMajorBit) { Nested nm(m.derived()); internal::evaluator thisEval(nm); // compute global width std::size_t width = 0; { std::ostringstream ss0; ss0.copyfmt(s); ss0 << Scalar(0); width = ss0.str().size(); for (Index row = 0; row < nm.outerSize(); ++row) { for (typename internal::evaluator::InnerIterator it(thisEval, row); it; ++it) { std::ostringstream ss; ss.copyfmt(s); ss << it.value(); const std::size_t potential_width = ss.str().size(); if (potential_width > width) width = potential_width; } } } for (Index row = 0; row < nm.outerSize(); ++row) { Index col = 0; for (typename internal::evaluator::InnerIterator it(thisEval, row); it; ++it) { for (; col < it.index(); ++col) { s.width(width); s << Scalar(0) << " "; } s.width(width); s << it.value() << " "; ++col; } for (; col < m.cols(); ++col) { s.width(width); s << Scalar(0) << " "; } s << std::endl; } } else { Nested nm(m.derived()); internal::evaluator thisEval(nm); if (m.cols() == 1) { // compute local width (single col) std::size_t width = 0; { std::ostringstream ss0; ss0.copyfmt(s); ss0 << Scalar(0); width = ss0.str().size(); for (typename internal::evaluator::InnerIterator it(thisEval, 0); it; ++it) { std::ostringstream ss; ss.copyfmt(s); ss << it.value(); const std::size_t potential_width = ss.str().size(); if (potential_width > width) width = potential_width; } } Index row = 0; for (typename internal::evaluator::InnerIterator it(thisEval, 0); it; ++it) { for (; row < it.index(); ++row) { s.width(width); s << Scalar(0) << std::endl; } s.width(width); s << it.value() << std::endl; ++row; } for (; row < m.rows(); ++row) { s.width(width); s << Scalar(0) << std::endl; } } else { SparseMatrix trans = m; s << static_cast >&>(trans); } } return s; } #endif template Derived& operator+=(const SparseMatrixBase& other); template Derived& operator-=(const SparseMatrixBase& other); template Derived& operator+=(const DiagonalBase& other); template Derived& operator-=(const DiagonalBase& other); template Derived& operator+=(const EigenBase& other); template Derived& operator-=(const EigenBase& other); Derived& operator*=(const Scalar& other); Derived& operator/=(const Scalar& other); template struct CwiseProductDenseReturnType { typedef CwiseBinaryOp< internal::scalar_product_op::Scalar, typename internal::traits::Scalar>::ReturnType>, const Derived, const OtherDerived> Type; }; template EIGEN_STRONG_INLINE const typename CwiseProductDenseReturnType::Type cwiseProduct( const MatrixBase& other) const; // sparse * diagonal template const Product operator*(const DiagonalBase& other) const { return Product(derived(), other.derived()); } // diagonal * sparse template friend const Product operator*(const DiagonalBase& lhs, const SparseMatrixBase& rhs) { return Product(lhs.derived(), rhs.derived()); } // sparse * sparse template const Product operator*(const SparseMatrixBase& other) const; // sparse * dense template const Product operator*(const MatrixBase& other) const { return Product(derived(), other.derived()); } // dense * sparse template friend const Product operator*(const MatrixBase& lhs, const SparseMatrixBase& rhs) { return Product(lhs.derived(), rhs.derived()); } /** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */ SparseSymmetricPermutationProduct twistedBy( const PermutationMatrix& perm) const { return SparseSymmetricPermutationProduct(derived(), perm); } template Derived& operator*=(const SparseMatrixBase& other); template inline const TriangularView triangularView() const; template struct SelfAdjointViewReturnType { typedef SparseSelfAdjointView Type; }; template struct ConstSelfAdjointViewReturnType { typedef const SparseSelfAdjointView Type; }; template inline typename ConstSelfAdjointViewReturnType::Type selfadjointView() const; template inline typename SelfAdjointViewReturnType::Type selfadjointView(); template Scalar dot(const MatrixBase& other) const; template Scalar dot(const SparseMatrixBase& other) const; RealScalar squaredNorm() const; RealScalar norm() const; RealScalar blueNorm() const; TransposeReturnType transpose() { return TransposeReturnType(derived()); } const ConstTransposeReturnType transpose() const { return ConstTransposeReturnType(derived()); } const AdjointReturnType adjoint() const { return AdjointReturnType(transpose()); } DenseMatrixType toDense() const { return DenseMatrixType(derived()); } template bool isApprox(const SparseMatrixBase& other, const RealScalar& prec = NumTraits::dummy_precision()) const; template bool isApprox(const MatrixBase& other, const RealScalar& prec = NumTraits::dummy_precision()) const { return toDense().isApprox(other, prec); } /** \returns the matrix or vector obtained by evaluating this expression. * * Notice that in the case of a plain matrix or vector (not an expression) this function just returns * a const reference, in order to avoid a useless copy. */ inline const typename internal::eval::type eval() const { return typename internal::eval::type(derived()); } Scalar sum() const; inline const SparseView pruned(const Scalar& reference = Scalar(0), const RealScalar& epsilon = NumTraits::dummy_precision()) const; protected: bool m_isRValue; static inline StorageIndex convert_index(const Index idx) { return internal::convert_index(idx); } private: template void evalTo(Dest&) const; }; } // end namespace Eigen #endif // EIGEN_SPARSEMATRIXBASE_H