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https://gitlab.com/libeigen/eigen.git
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039408cd66
added function for array.min(), array.max(), matrix.cwiseMin(), matrix.cwiseMax(). The matrix.cwiseMin/Max functions required the definition of the ConstantReturnType typedef. However, it wasn't defined until after MatrixCwiseBinaryOps was included in Eigen/src/SparseCore/SparseMatrixBase.h, so I moved those includes after the definition of the typedefs. tests for both the regular and scalar min/max functions were added as well
466 lines
19 KiB
C++
466 lines
19 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.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_SPARSEMATRIXBASE_H
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#define EIGEN_SPARSEMATRIXBASE_H
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/** \ingroup SparseCore_Module
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*
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* \class SparseMatrixBase
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*
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* \brief Base class of any sparse matrices or sparse expressions
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*
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* \tparam Derived
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*
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* This class can be extended with the help of the plugin mechanism described on the page
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* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN.
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*/
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template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
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{
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public:
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typedef typename internal::traits<Derived>::Scalar Scalar;
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typedef typename internal::packet_traits<Scalar>::type PacketScalar;
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typedef typename internal::traits<Derived>::StorageKind StorageKind;
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typedef typename internal::traits<Derived>::Index Index;
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typedef typename internal::add_const_on_value_type_if_arithmetic<
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typename internal::packet_traits<Scalar>::type
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>::type PacketReturnType;
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typedef SparseMatrixBase StorageBaseType;
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typedef EigenBase<Derived> Base;
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template<typename OtherDerived>
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Derived& operator=(const EigenBase<OtherDerived> &other)
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{
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other.derived().evalTo(derived());
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return derived();
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}
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enum {
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RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
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/**< The number of rows at compile-time. This is just a copy of the value provided
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* by the \a Derived type. If a value is not known at compile-time,
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* it is set to the \a Dynamic constant.
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* \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */
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ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
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/**< The number of columns at compile-time. This is just a copy of the value provided
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* by the \a Derived type. If a value is not known at compile-time,
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* it is set to the \a Dynamic constant.
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* \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
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SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
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internal::traits<Derived>::ColsAtCompileTime>::ret),
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/**< This is equal to the number of coefficients, i.e. the number of
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* rows times the number of columns, or to \a Dynamic if this is not
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* known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
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MaxRowsAtCompileTime = RowsAtCompileTime,
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MaxColsAtCompileTime = ColsAtCompileTime,
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MaxSizeAtCompileTime = (internal::size_at_compile_time<MaxRowsAtCompileTime,
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MaxColsAtCompileTime>::ret),
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IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1,
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/**< This is set to true if either the number of rows or the number of
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* columns is known at compile-time to be equal to 1. Indeed, in that case,
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* we are dealing with a column-vector (if there is only one column) or with
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* a row-vector (if there is only one row). */
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Flags = internal::traits<Derived>::Flags,
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/**< This stores expression \ref flags flags which may or may not be inherited by new expressions
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* constructed from this one. See the \ref flags "list of flags".
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*/
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CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
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/**< This is a rough measure of how expensive it is to read one coefficient from
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* this expression.
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*/
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IsRowMajor = Flags&RowMajorBit ? 1 : 0,
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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_HasDirectAccess = (int(Flags)&DirectAccessBit) ? 1 : 0 // workaround sunCC
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#endif
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};
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/** \internal the return type of MatrixBase::adjoint() */
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typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
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CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Eigen::Transpose<const Derived> >,
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Transpose<const Derived>
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>::type AdjointReturnType;
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typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor> PlainObject;
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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/** This is the "real scalar" type; if the \a Scalar type is already real numbers
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* (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
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* \a Scalar is \a std::complex<T> then RealScalar is \a T.
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*
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* \sa class NumTraits
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*/
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typedef typename NumTraits<Scalar>::Real RealScalar;
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/** \internal the return type of coeff()
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*/
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typedef typename internal::conditional<_HasDirectAccess, const Scalar&, Scalar>::type CoeffReturnType;
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/** \internal Represents a matrix with all coefficients equal to one another*/
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typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Matrix<Scalar,Dynamic,Dynamic> > ConstantReturnType;
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/** type of the equivalent square matrix */
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typedef Matrix<Scalar,EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime),
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EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType;
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inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
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inline Derived& derived() { return *static_cast<Derived*>(this); }
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inline Derived& const_cast_derived() const
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{ return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }
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#endif // not EIGEN_PARSED_BY_DOXYGEN
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#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
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# include "../plugins/CommonCwiseUnaryOps.h"
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# include "../plugins/CommonCwiseBinaryOps.h"
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# include "../plugins/MatrixCwiseUnaryOps.h"
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# include "../plugins/MatrixCwiseBinaryOps.h"
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# ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN
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# include EIGEN_SPARSEMATRIXBASE_PLUGIN
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# endif
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# undef EIGEN_CURRENT_STORAGE_BASE_CLASS
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#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
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/** \returns the number of rows. \sa cols() */
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inline Index rows() const { return derived().rows(); }
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/** \returns the number of columns. \sa rows() */
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inline Index cols() const { return derived().cols(); }
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/** \returns the number of coefficients, which is \a rows()*cols().
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* \sa rows(), cols(). */
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inline Index size() const { return rows() * cols(); }
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/** \returns the number of nonzero coefficients which is in practice the number
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* of stored coefficients. */
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inline Index nonZeros() const { return derived().nonZeros(); }
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/** \returns true if either the number of rows or the number of columns is equal to 1.
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* In other words, this function returns
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* \code rows()==1 || cols()==1 \endcode
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* \sa rows(), cols(), IsVectorAtCompileTime. */
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inline bool isVector() const { return rows()==1 || cols()==1; }
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/** \returns the size of the storage major dimension,
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* i.e., the number of columns for a columns major matrix, and the number of rows otherwise */
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Index outerSize() const { return (int(Flags)&RowMajorBit) ? this->rows() : this->cols(); }
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/** \returns the size of the inner dimension according to the storage order,
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* i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
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Index innerSize() const { return (int(Flags)&RowMajorBit) ? this->cols() : this->rows(); }
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bool isRValue() const { return m_isRValue; }
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Derived& markAsRValue() { m_isRValue = true; return derived(); }
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SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ }
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template<typename OtherDerived>
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Derived& operator=(const ReturnByValue<OtherDerived>& other)
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{
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other.evalTo(derived());
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return derived();
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}
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template<typename OtherDerived>
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inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other)
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{
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return assign(other.derived());
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}
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inline Derived& operator=(const Derived& other)
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{
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// if (other.isRValue())
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// derived().swap(other.const_cast_derived());
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// else
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return assign(other.derived());
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}
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protected:
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template<typename OtherDerived>
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inline Derived& assign(const OtherDerived& other)
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{
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const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
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const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
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if ((!transpose) && other.isRValue())
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{
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// eval without temporary
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derived().resize(other.rows(), other.cols());
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derived().setZero();
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derived().reserve((std::max)(this->rows(),this->cols())*2);
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for (Index j=0; j<outerSize; ++j)
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{
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derived().startVec(j);
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for (typename OtherDerived::InnerIterator it(other, j); it; ++it)
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{
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Scalar v = it.value();
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if (v!=Scalar(0))
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derived().insertBackByOuterInner(j,it.index()) = v;
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}
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}
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derived().finalize();
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}
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else
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{
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assignGeneric(other);
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}
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return derived();
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}
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template<typename OtherDerived>
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inline void assignGeneric(const OtherDerived& other)
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{
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//const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
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eigen_assert(( ((internal::traits<Derived>::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
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(!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) &&
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"the transpose operation is supposed to be handled in SparseMatrix::operator=");
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enum { Flip = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit) };
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const Index outerSize = other.outerSize();
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//typedef typename internal::conditional<transpose, LinkedVectorMatrix<Scalar,Flags&RowMajorBit>, Derived>::type TempType;
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// thanks to shallow copies, we always eval to a tempary
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Derived temp(other.rows(), other.cols());
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temp.reserve((std::max)(this->rows(),this->cols())*2);
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for (Index j=0; j<outerSize; ++j)
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{
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temp.startVec(j);
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for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
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{
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Scalar v = it.value();
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if (v!=Scalar(0))
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temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
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}
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}
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temp.finalize();
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derived() = temp.markAsRValue();
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}
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public:
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template<typename Lhs, typename Rhs>
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inline Derived& operator=(const SparseSparseProduct<Lhs,Rhs>& product);
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friend std::ostream & operator << (std::ostream & s, const SparseMatrixBase& m)
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{
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typedef typename Derived::Nested Nested;
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typedef typename internal::remove_all<Nested>::type NestedCleaned;
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if (Flags&RowMajorBit)
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{
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const Nested nm(m.derived());
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for (Index row=0; row<nm.outerSize(); ++row)
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{
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Index col = 0;
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for (typename NestedCleaned::InnerIterator it(nm.derived(), row); it; ++it)
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{
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for ( ; col<it.index(); ++col)
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s << "0 ";
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s << it.value() << " ";
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++col;
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}
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for ( ; col<m.cols(); ++col)
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s << "0 ";
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s << std::endl;
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}
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}
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else
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{
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const Nested nm(m.derived());
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if (m.cols() == 1) {
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Index row = 0;
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for (typename NestedCleaned::InnerIterator it(nm.derived(), 0); it; ++it)
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{
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for ( ; row<it.index(); ++row)
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s << "0" << std::endl;
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s << it.value() << std::endl;
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++row;
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}
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for ( ; row<m.rows(); ++row)
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s << "0" << std::endl;
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}
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else
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{
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SparseMatrix<Scalar, RowMajorBit> trans = m;
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s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit> >&>(trans);
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}
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}
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return s;
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}
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template<typename OtherDerived>
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Derived& operator+=(const SparseMatrixBase<OtherDerived>& other);
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template<typename OtherDerived>
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Derived& operator-=(const SparseMatrixBase<OtherDerived>& other);
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Derived& operator*=(const Scalar& other);
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Derived& operator/=(const Scalar& other);
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#define EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE \
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CwiseBinaryOp< \
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internal::scalar_product_op< \
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typename internal::scalar_product_traits< \
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typename internal::traits<Derived>::Scalar, \
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typename internal::traits<OtherDerived>::Scalar \
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>::ReturnType \
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>, \
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Derived, \
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OtherDerived \
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>
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
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cwiseProduct(const MatrixBase<OtherDerived> &other) const;
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// sparse * sparse
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template<typename OtherDerived>
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const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
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operator*(const SparseMatrixBase<OtherDerived> &other) const;
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// sparse * diagonal
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template<typename OtherDerived>
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const SparseDiagonalProduct<Derived,OtherDerived>
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operator*(const DiagonalBase<OtherDerived> &other) const;
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// diagonal * sparse
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template<typename OtherDerived> friend
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const SparseDiagonalProduct<OtherDerived,Derived>
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operator*(const DiagonalBase<OtherDerived> &lhs, const SparseMatrixBase& rhs)
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{ return SparseDiagonalProduct<OtherDerived,Derived>(lhs.derived(), rhs.derived()); }
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/** dense * sparse (return a dense object unless it is an outer product) */
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template<typename OtherDerived> friend
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const typename DenseSparseProductReturnType<OtherDerived,Derived>::Type
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operator*(const MatrixBase<OtherDerived>& lhs, const Derived& rhs)
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{ return typename DenseSparseProductReturnType<OtherDerived,Derived>::Type(lhs.derived(),rhs); }
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/** sparse * dense (returns a dense object unless it is an outer product) */
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template<typename OtherDerived>
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const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type
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operator*(const MatrixBase<OtherDerived> &other) const;
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template<typename OtherDerived>
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Derived& operator*=(const SparseMatrixBase<OtherDerived>& other);
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#ifdef EIGEN2_SUPPORT
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// deprecated
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template<typename OtherDerived>
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typename internal::plain_matrix_type_column_major<OtherDerived>::type
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solveTriangular(const MatrixBase<OtherDerived>& other) const;
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// deprecated
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template<typename OtherDerived>
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void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const;
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#endif // EIGEN2_SUPPORT
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template<int Mode>
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inline const SparseTriangularView<Derived, Mode> triangularView() const;
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template<unsigned int UpLo> inline const SparseSelfAdjointView<Derived, UpLo> selfadjointView() const;
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template<unsigned int UpLo> inline SparseSelfAdjointView<Derived, UpLo> selfadjointView();
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template<typename OtherDerived> Scalar dot(const MatrixBase<OtherDerived>& other) const;
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template<typename OtherDerived> Scalar dot(const SparseMatrixBase<OtherDerived>& other) const;
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RealScalar squaredNorm() const;
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RealScalar norm() const;
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Transpose<Derived> transpose() { return derived(); }
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const Transpose<const Derived> transpose() const { return derived(); }
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const AdjointReturnType adjoint() const { return transpose(); }
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// sub-vector
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SparseInnerVectorSet<Derived,1> row(Index i);
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const SparseInnerVectorSet<Derived,1> row(Index i) const;
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SparseInnerVectorSet<Derived,1> col(Index j);
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const SparseInnerVectorSet<Derived,1> col(Index j) const;
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SparseInnerVectorSet<Derived,1> innerVector(Index outer);
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const SparseInnerVectorSet<Derived,1> innerVector(Index outer) const;
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// set of sub-vectors
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SparseInnerVectorSet<Derived,Dynamic> subrows(Index start, Index size);
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const SparseInnerVectorSet<Derived,Dynamic> subrows(Index start, Index size) const;
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SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size);
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const SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size) const;
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SparseInnerVectorSet<Derived,Dynamic> middleRows(Index start, Index size);
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const SparseInnerVectorSet<Derived,Dynamic> middleRows(Index start, Index size) const;
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SparseInnerVectorSet<Derived,Dynamic> middleCols(Index start, Index size);
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const SparseInnerVectorSet<Derived,Dynamic> middleCols(Index start, Index size) const;
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SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize);
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const SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize) const;
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/** \internal use operator= */
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template<typename DenseDerived>
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void evalTo(MatrixBase<DenseDerived>& dst) const
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{
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dst.setZero();
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for (Index j=0; j<outerSize(); ++j)
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for (typename Derived::InnerIterator i(derived(),j); i; ++i)
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dst.coeffRef(i.row(),i.col()) = i.value();
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}
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Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> toDense() const
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{
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return derived();
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}
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template<typename OtherDerived>
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bool isApprox(const SparseMatrixBase<OtherDerived>& other,
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RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
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{ return toDense().isApprox(other.toDense(),prec); }
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template<typename OtherDerived>
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bool isApprox(const MatrixBase<OtherDerived>& other,
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RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
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{ return toDense().isApprox(other,prec); }
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/** \returns the matrix or vector obtained by evaluating this expression.
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*
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* Notice that in the case of a plain matrix or vector (not an expression) this function just returns
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* a const reference, in order to avoid a useless copy.
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*/
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inline const typename internal::eval<Derived>::type eval() const
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{ return typename internal::eval<Derived>::type(derived()); }
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Scalar sum() const;
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protected:
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bool m_isRValue;
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};
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#endif // EIGEN_SPARSEMATRIXBASE_H
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