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Refactor folder (#10475)
Move many third-party components' source codes from the src folder to a new folder called deps_src. The goal is to make the code structure clearer and easier to navigate.
This commit is contained in:
327
deps_src/eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h
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327
deps_src/eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h
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// 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 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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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_RANDOMSETTER_H
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#define EIGEN_RANDOMSETTER_H
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namespace Eigen {
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/** Represents a std::map
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*
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* \see RandomSetter
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*/
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template<typename Scalar> struct StdMapTraits
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{
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typedef int KeyType;
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typedef std::map<KeyType,Scalar> Type;
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enum {
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IsSorted = 1
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};
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static void setInvalidKey(Type&, const KeyType&) {}
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};
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#ifdef EIGEN_UNORDERED_MAP_SUPPORT
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/** Represents a std::unordered_map
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*
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* To use it you need to both define EIGEN_UNORDERED_MAP_SUPPORT and include the unordered_map header file
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* yourself making sure that unordered_map is defined in the std namespace.
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*
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* For instance, with current version of gcc you can either enable C++0x standard (-std=c++0x) or do:
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* \code
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* #include <tr1/unordered_map>
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* #define EIGEN_UNORDERED_MAP_SUPPORT
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* namespace std {
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* using std::tr1::unordered_map;
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* }
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* \endcode
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*
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* \see RandomSetter
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*/
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template<typename Scalar> struct StdUnorderedMapTraits
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{
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typedef int KeyType;
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typedef std::unordered_map<KeyType,Scalar> Type;
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enum {
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IsSorted = 0
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};
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static void setInvalidKey(Type&, const KeyType&) {}
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};
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#endif // EIGEN_UNORDERED_MAP_SUPPORT
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#ifdef _DENSE_HASH_MAP_H_
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/** Represents a google::dense_hash_map
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*
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* \see RandomSetter
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*/
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template<typename Scalar> struct GoogleDenseHashMapTraits
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{
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typedef int KeyType;
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typedef google::dense_hash_map<KeyType,Scalar> Type;
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enum {
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IsSorted = 0
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};
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static void setInvalidKey(Type& map, const KeyType& k)
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{ map.set_empty_key(k); }
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};
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#endif
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#ifdef _SPARSE_HASH_MAP_H_
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/** Represents a google::sparse_hash_map
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*
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* \see RandomSetter
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*/
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template<typename Scalar> struct GoogleSparseHashMapTraits
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{
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typedef int KeyType;
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typedef google::sparse_hash_map<KeyType,Scalar> Type;
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enum {
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IsSorted = 0
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};
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static void setInvalidKey(Type&, const KeyType&) {}
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};
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#endif
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/** \class RandomSetter
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*
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* \brief The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
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*
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* \tparam SparseMatrixType the type of the sparse matrix we are updating
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* \tparam MapTraits a traits class representing the map implementation used for the temporary sparse storage.
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* Its default value depends on the system.
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* \tparam OuterPacketBits defines the number of rows (or columns) manage by a single map object
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* as a power of two exponent.
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*
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* This class temporarily represents a sparse matrix object using a generic map implementation allowing for
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* efficient random access. The conversion from the compressed representation to a hash_map object is performed
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* in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy
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* suggest the use of nested blocks as in this example:
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*
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* \code
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* SparseMatrix<double> m(rows,cols);
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* {
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* RandomSetter<SparseMatrix<double> > w(m);
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* // don't use m but w instead with read/write random access to the coefficients:
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* for(;;)
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* w(rand(),rand()) = rand;
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* }
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* // when w is deleted, the data are copied back to m
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* // and m is ready to use.
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* \endcode
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*
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* Since hash_map objects are not fully sorted, representing a full matrix as a single hash_map would
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* involve a big and costly sort to update the compressed matrix back. To overcome this issue, a RandomSetter
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* use multiple hash_map, each representing 2^OuterPacketBits columns or rows according to the storage order.
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* To reach optimal performance, this value should be adjusted according to the average number of nonzeros
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* per rows/columns.
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*
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* The possible values for the template parameter MapTraits are:
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* - \b StdMapTraits: corresponds to std::map. (does not perform very well)
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* - \b GnuHashMapTraits: corresponds to __gnu_cxx::hash_map (available only with GCC)
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* - \b GoogleDenseHashMapTraits: corresponds to google::dense_hash_map (best efficiency, reasonable memory consumption)
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* - \b GoogleSparseHashMapTraits: corresponds to google::sparse_hash_map (best memory consumption, relatively good performance)
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*
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* The default map implementation depends on the availability, and the preferred order is:
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* GoogleSparseHashMapTraits, GnuHashMapTraits, and finally StdMapTraits.
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*
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* For performance and memory consumption reasons it is highly recommended to use one of
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* the Google's hash_map implementation. To enable the support for them, you have two options:
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* - \#include <google/dense_hash_map> yourself \b before Eigen/Sparse header
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* - define EIGEN_GOOGLEHASH_SUPPORT
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* In the later case the inclusion of <google/dense_hash_map> is made for you.
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*
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* \see http://code.google.com/p/google-sparsehash/
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*/
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template<typename SparseMatrixType,
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template <typename T> class MapTraits =
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#if defined _DENSE_HASH_MAP_H_
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GoogleDenseHashMapTraits
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#elif defined _HASH_MAP
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GnuHashMapTraits
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#else
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StdMapTraits
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#endif
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,int OuterPacketBits = 6>
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class RandomSetter
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{
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typedef typename SparseMatrixType::Scalar Scalar;
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typedef typename SparseMatrixType::StorageIndex StorageIndex;
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struct ScalarWrapper
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{
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ScalarWrapper() : value(0) {}
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Scalar value;
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};
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typedef typename MapTraits<ScalarWrapper>::KeyType KeyType;
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typedef typename MapTraits<ScalarWrapper>::Type HashMapType;
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static const int OuterPacketMask = (1 << OuterPacketBits) - 1;
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enum {
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SwapStorage = 1 - MapTraits<ScalarWrapper>::IsSorted,
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TargetRowMajor = (SparseMatrixType::Flags & RowMajorBit) ? 1 : 0,
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SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor
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};
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public:
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/** Constructs a random setter object from the sparse matrix \a target
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*
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* Note that the initial value of \a target are imported. If you want to re-set
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* a sparse matrix from scratch, then you must set it to zero first using the
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* setZero() function.
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*/
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inline RandomSetter(SparseMatrixType& target)
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: mp_target(&target)
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{
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const Index outerSize = SwapStorage ? target.innerSize() : target.outerSize();
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const Index innerSize = SwapStorage ? target.outerSize() : target.innerSize();
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m_outerPackets = outerSize >> OuterPacketBits;
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if (outerSize&OuterPacketMask)
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m_outerPackets += 1;
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m_hashmaps = new HashMapType[m_outerPackets];
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// compute number of bits needed to store inner indices
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Index aux = innerSize - 1;
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m_keyBitsOffset = 0;
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while (aux)
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{
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++m_keyBitsOffset;
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aux = aux >> 1;
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}
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KeyType ik = (1<<(OuterPacketBits+m_keyBitsOffset));
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for (Index k=0; k<m_outerPackets; ++k)
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MapTraits<ScalarWrapper>::setInvalidKey(m_hashmaps[k],ik);
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// insert current coeffs
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for (Index j=0; j<mp_target->outerSize(); ++j)
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for (typename SparseMatrixType::InnerIterator it(*mp_target,j); it; ++it)
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(*this)(TargetRowMajor?j:it.index(), TargetRowMajor?it.index():j) = it.value();
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}
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/** Destructor updating back the sparse matrix target */
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~RandomSetter()
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{
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KeyType keyBitsMask = (1<<m_keyBitsOffset)-1;
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if (!SwapStorage) // also means the map is sorted
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{
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mp_target->setZero();
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mp_target->makeCompressed();
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mp_target->reserve(nonZeros());
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Index prevOuter = -1;
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for (Index k=0; k<m_outerPackets; ++k)
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{
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const Index outerOffset = (1<<OuterPacketBits) * k;
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typename HashMapType::iterator end = m_hashmaps[k].end();
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for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
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{
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const Index outer = (it->first >> m_keyBitsOffset) + outerOffset;
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const Index inner = it->first & keyBitsMask;
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if (prevOuter!=outer)
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{
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for (Index j=prevOuter+1;j<=outer;++j)
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mp_target->startVec(j);
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prevOuter = outer;
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}
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mp_target->insertBackByOuterInner(outer, inner) = it->second.value;
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}
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}
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mp_target->finalize();
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}
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else
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{
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VectorXi positions(mp_target->outerSize());
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positions.setZero();
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// pass 1
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for (Index k=0; k<m_outerPackets; ++k)
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{
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typename HashMapType::iterator end = m_hashmaps[k].end();
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for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
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{
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const Index outer = it->first & keyBitsMask;
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++positions[outer];
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}
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}
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// prefix sum
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Index count = 0;
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for (Index j=0; j<mp_target->outerSize(); ++j)
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{
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Index tmp = positions[j];
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mp_target->outerIndexPtr()[j] = count;
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positions[j] = count;
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count += tmp;
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}
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mp_target->makeCompressed();
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mp_target->outerIndexPtr()[mp_target->outerSize()] = count;
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mp_target->resizeNonZeros(count);
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// pass 2
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for (Index k=0; k<m_outerPackets; ++k)
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{
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const Index outerOffset = (1<<OuterPacketBits) * k;
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typename HashMapType::iterator end = m_hashmaps[k].end();
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for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
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{
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const Index inner = (it->first >> m_keyBitsOffset) + outerOffset;
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const Index outer = it->first & keyBitsMask;
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// sorted insertion
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// Note that we have to deal with at most 2^OuterPacketBits unsorted coefficients,
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// moreover those 2^OuterPacketBits coeffs are likely to be sparse, an so only a
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// small fraction of them have to be sorted, whence the following simple procedure:
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Index posStart = mp_target->outerIndexPtr()[outer];
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Index i = (positions[outer]++) - 1;
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while ( (i >= posStart) && (mp_target->innerIndexPtr()[i] > inner) )
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{
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mp_target->valuePtr()[i+1] = mp_target->valuePtr()[i];
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mp_target->innerIndexPtr()[i+1] = mp_target->innerIndexPtr()[i];
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--i;
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}
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mp_target->innerIndexPtr()[i+1] = inner;
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mp_target->valuePtr()[i+1] = it->second.value;
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}
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}
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}
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delete[] m_hashmaps;
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}
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/** \returns a reference to the coefficient at given coordinates \a row, \a col */
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Scalar& operator() (Index row, Index col)
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{
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const Index outer = SetterRowMajor ? row : col;
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const Index inner = SetterRowMajor ? col : row;
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const Index outerMajor = outer >> OuterPacketBits; // index of the packet/map
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const Index outerMinor = outer & OuterPacketMask; // index of the inner vector in the packet
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const KeyType key = internal::convert_index<KeyType>((outerMinor<<m_keyBitsOffset) | inner);
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return m_hashmaps[outerMajor][key].value;
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}
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/** \returns the number of non zero coefficients
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*
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* \note According to the underlying map/hash_map implementation,
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* this function might be quite expensive.
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*/
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Index nonZeros() const
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{
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Index nz = 0;
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for (Index k=0; k<m_outerPackets; ++k)
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nz += static_cast<Index>(m_hashmaps[k].size());
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return nz;
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}
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protected:
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HashMapType* m_hashmaps;
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SparseMatrixType* mp_target;
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Index m_outerPackets;
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unsigned char m_keyBitsOffset;
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};
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} // end namespace Eigen
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#endif // EIGEN_RANDOMSETTER_H
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