208 lines
6.1 KiB
C
208 lines
6.1 KiB
C
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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) 2008-2011 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_TESTSPARSE_H
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#define EIGEN_TESTSPARSE_H
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#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
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#include "main.h"
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#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC && !defined(__clang__)
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#ifdef min
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#undef min
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#endif
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#ifdef max
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#undef max
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#endif
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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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#endif
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#ifdef EIGEN_GOOGLEHASH_SUPPORT
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#include <google/sparse_hash_map>
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#endif
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#include <Eigen/Cholesky>
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#include <Eigen/LU>
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#include <Eigen/Sparse>
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enum {
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ForceNonZeroDiag = 1,
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MakeLowerTriangular = 2,
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MakeUpperTriangular = 4,
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ForceRealDiag = 8
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};
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/* Initializes both a sparse and dense matrix with same random values,
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* and a ratio of \a density non zero entries.
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* \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
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* allowing to control the shape of the matrix.
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* \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
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* and zero coefficients respectively.
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*/
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template<typename Scalar,int Opt1,int Opt2,typename Index> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat,
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SparseMatrix<Scalar,Opt2,Index>& sparseMat,
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int flags = 0,
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std::vector<Matrix<Index,2,1> >* zeroCoords = 0,
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std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0)
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{
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enum { IsRowMajor = SparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
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sparseMat.setZero();
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//sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
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sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows()))));
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for(Index j=0; j<sparseMat.outerSize(); j++)
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{
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//sparseMat.startVec(j);
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for(Index i=0; i<sparseMat.innerSize(); i++)
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{
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int ai(i), aj(j);
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if(IsRowMajor)
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std::swap(ai,aj);
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Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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if ((flags&ForceNonZeroDiag) && (i==j))
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{
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v = internal::random<Scalar>()*Scalar(3.);
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v = v*v + Scalar(5.);
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}
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if ((flags & MakeLowerTriangular) && aj>ai)
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v = Scalar(0);
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else if ((flags & MakeUpperTriangular) && aj<ai)
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v = Scalar(0);
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if ((flags&ForceRealDiag) && (i==j))
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v = numext::real(v);
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if (v!=Scalar(0))
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{
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//sparseMat.insertBackByOuterInner(j,i) = v;
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sparseMat.insertByOuterInner(j,i) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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}
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else if (zeroCoords)
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{
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zeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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}
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refMat(ai,aj) = v;
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}
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}
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//sparseMat.finalize();
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}
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template<typename Scalar,int Opt1,int Opt2,typename Index> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,Dynamic, Opt1>& refMat,
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DynamicSparseMatrix<Scalar, Opt2, Index>& sparseMat,
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int flags = 0,
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std::vector<Matrix<Index,2,1> >* zeroCoords = 0,
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std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0)
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{
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enum { IsRowMajor = DynamicSparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
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sparseMat.setZero();
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sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
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for(int j=0; j<sparseMat.outerSize(); j++)
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{
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sparseMat.startVec(j); // not needed for DynamicSparseMatrix
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for(int i=0; i<sparseMat.innerSize(); i++)
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{
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int ai(i), aj(j);
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if(IsRowMajor)
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std::swap(ai,aj);
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Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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if ((flags&ForceNonZeroDiag) && (i==j))
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{
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v = internal::random<Scalar>()*Scalar(3.);
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v = v*v + Scalar(5.);
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}
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if ((flags & MakeLowerTriangular) && aj>ai)
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v = Scalar(0);
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else if ((flags & MakeUpperTriangular) && aj<ai)
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v = Scalar(0);
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if ((flags&ForceRealDiag) && (i==j))
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v = numext::real(v);
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if (v!=Scalar(0))
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{
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sparseMat.insertBackByOuterInner(j,i) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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}
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else if (zeroCoords)
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{
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zeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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}
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refMat(ai,aj) = v;
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}
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}
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sparseMat.finalize();
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}
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template<typename Scalar,int Options,typename Index> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,1>& refVec,
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SparseVector<Scalar,Options,Index>& sparseVec,
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std::vector<int>* zeroCoords = 0,
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std::vector<int>* nonzeroCoords = 0)
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{
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sparseVec.reserve(int(refVec.size()*density));
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sparseVec.setZero();
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for(Index i=0; i<refVec.size(); i++)
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{
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Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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if (v!=Scalar(0))
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{
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sparseVec.insertBack(i) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(i);
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}
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else if (zeroCoords)
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zeroCoords->push_back(i);
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refVec[i] = v;
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}
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}
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template<typename Scalar,int Options,typename Index> void
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initSparse(double density,
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Matrix<Scalar,1,Dynamic>& refVec,
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SparseVector<Scalar,Options,Index>& sparseVec,
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std::vector<int>* zeroCoords = 0,
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std::vector<int>* nonzeroCoords = 0)
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{
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sparseVec.reserve(int(refVec.size()*density));
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sparseVec.setZero();
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for(int i=0; i<refVec.size(); i++)
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{
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Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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if (v!=Scalar(0))
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{
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sparseVec.insertBack(i) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(i);
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}
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else if (zeroCoords)
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zeroCoords->push_back(i);
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refVec[i] = v;
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}
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}
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#include <unsupported/Eigen/SparseExtra>
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#endif // EIGEN_TESTSPARSE_H
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