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fb3438e609
- add cwiseExp(), cwiseLog()...
--> for example, doing a gamma-correction on a bitmap image stored as
an array of floats is a simple matter of:
Eigen::Map<VectorXf> m = VectorXf::map(bitmap,size);
m = m.cwisePow(gamma);
- apidoc improvements, reorganization of the \name's
- remove obsolete examples
- remove EIGEN_ALWAYS_INLINE on lazyProduct(), it seems useless.
78 lines
3.1 KiB
C++
78 lines
3.1 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_FORWARDDECLARATIONS_H
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#define EIGEN_FORWARDDECLARATIONS_H
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template<typename T> struct ei_traits;
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template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols> class Matrix;
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template<typename MatrixType> class MatrixRef;
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template<typename MatrixType> class Minor;
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template<typename MatrixType, int BlockRows=Dynamic, int BlockCols=Dynamic> class Block;
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template<typename MatrixType> class Transpose;
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template<typename MatrixType> class Conjugate;
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template<typename BinaryOp, typename Lhs, typename Rhs> class CwiseBinaryOp;
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template<typename UnaryOp, typename MatrixType> class CwiseUnaryOp;
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template<typename Lhs, typename Rhs> class Product;
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template<typename MatrixType> class Random;
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template<typename MatrixType> class Zero;
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template<typename MatrixType> class Ones;
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template<typename CoeffsVectorType> class DiagonalMatrix;
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template<typename MatrixType> class DiagonalCoeffs;
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template<typename MatrixType> class Identity;
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template<typename MatrixType> class Map;
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template<typename Derived> class Eval;
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template<typename Derived> class EvalOMP;
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struct ei_scalar_sum_op;
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struct ei_scalar_difference_op;
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struct ei_scalar_product_op;
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struct ei_scalar_quotient_op;
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struct ei_scalar_opposite_op;
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struct ei_scalar_conjugate_op;
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struct ei_scalar_abs_op;
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struct ei_scalar_abs2_op;
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struct ei_scalar_sqrt_op;
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struct ei_scalar_exp_op;
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struct ei_scalar_log_op;
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struct ei_scalar_cos_op;
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struct ei_scalar_sin_op;
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template<typename Scalar> struct ei_scalar_pow_op;
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template<typename NewType> struct ei_scalar_cast_op;
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template<typename Scalar> struct ei_scalar_multiple_op;
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template<typename T> struct ei_xpr_copy
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{
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typedef T Type;
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};
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template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols>
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struct ei_xpr_copy<Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _MaxRows, _MaxCols> >
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{
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typedef const Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _MaxRows, _MaxCols> & Type;
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};
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#endif // EIGEN_FORWARDDECLARATIONS_H
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