[136] | 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra.
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| 3 | //
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| 4 | // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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| 5 | //
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| 6 | // This Source Code Form is subject to the terms of the Mozilla
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| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 9 |
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| 10 | #ifndef EIGEN_TESTSPARSE_H
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| 11 | #define EIGEN_TESTSPARSE_H
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| 12 |
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| 13 | #define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
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| 14 |
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| 15 | #include "main.h"
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| 16 |
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| 17 | #if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC && !defined(__clang__)
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| 18 |
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| 19 | #ifdef min
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| 20 | #undef min
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| 21 | #endif
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| 22 |
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| 23 | #ifdef max
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| 24 | #undef max
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| 25 | #endif
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| 26 |
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| 27 | #include <tr1/unordered_map>
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| 28 | #define EIGEN_UNORDERED_MAP_SUPPORT
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| 29 | namespace std {
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| 30 | using std::tr1::unordered_map;
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| 31 | }
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| 32 | #endif
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| 33 |
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| 34 | #ifdef EIGEN_GOOGLEHASH_SUPPORT
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| 35 | #include <google/sparse_hash_map>
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| 36 | #endif
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| 37 |
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| 38 | #include <Eigen/Cholesky>
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| 39 | #include <Eigen/LU>
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| 40 | #include <Eigen/Sparse>
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| 41 |
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| 42 | enum {
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| 43 | ForceNonZeroDiag = 1,
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| 44 | MakeLowerTriangular = 2,
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| 45 | MakeUpperTriangular = 4,
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| 46 | ForceRealDiag = 8
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| 47 | };
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| 48 |
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| 49 | /* Initializes both a sparse and dense matrix with same random values,
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| 50 | * and a ratio of \a density non zero entries.
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| 51 | * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
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| 52 | * allowing to control the shape of the matrix.
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| 53 | * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
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| 54 | * and zero coefficients respectively.
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| 55 | */
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| 56 | template<typename Scalar,int Opt1,int Opt2,typename Index> void
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| 57 | initSparse(double density,
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| 58 | Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat,
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| 59 | SparseMatrix<Scalar,Opt2,Index>& sparseMat,
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| 60 | int flags = 0,
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| 61 | std::vector<Matrix<Index,2,1> >* zeroCoords = 0,
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| 62 | std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0)
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| 63 | {
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| 64 | enum { IsRowMajor = SparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
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| 65 | sparseMat.setZero();
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| 66 | //sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
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| 67 | sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows()))));
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| 68 |
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| 69 | for(Index j=0; j<sparseMat.outerSize(); j++)
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| 70 | {
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| 71 | //sparseMat.startVec(j);
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| 72 | for(Index i=0; i<sparseMat.innerSize(); i++)
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| 73 | {
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| 74 | int ai(i), aj(j);
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| 75 | if(IsRowMajor)
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| 76 | std::swap(ai,aj);
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| 77 | Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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| 78 | if ((flags&ForceNonZeroDiag) && (i==j))
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| 79 | {
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| 80 | v = internal::random<Scalar>()*Scalar(3.);
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| 81 | v = v*v + Scalar(5.);
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| 82 | }
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| 83 | if ((flags & MakeLowerTriangular) && aj>ai)
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| 84 | v = Scalar(0);
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| 85 | else if ((flags & MakeUpperTriangular) && aj<ai)
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| 86 | v = Scalar(0);
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| 87 |
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| 88 | if ((flags&ForceRealDiag) && (i==j))
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| 89 | v = numext::real(v);
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| 90 |
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| 91 | if (v!=Scalar(0))
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| 92 | {
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| 93 | //sparseMat.insertBackByOuterInner(j,i) = v;
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| 94 | sparseMat.insertByOuterInner(j,i) = v;
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| 95 | if (nonzeroCoords)
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| 96 | nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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| 97 | }
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| 98 | else if (zeroCoords)
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| 99 | {
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| 100 | zeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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| 101 | }
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| 102 | refMat(ai,aj) = v;
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| 103 | }
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| 104 | }
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| 105 | //sparseMat.finalize();
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| 106 | }
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| 107 |
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| 108 | template<typename Scalar,int Opt1,int Opt2,typename Index> void
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| 109 | initSparse(double density,
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| 110 | Matrix<Scalar,Dynamic,Dynamic, Opt1>& refMat,
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| 111 | DynamicSparseMatrix<Scalar, Opt2, Index>& sparseMat,
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| 112 | int flags = 0,
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| 113 | std::vector<Matrix<Index,2,1> >* zeroCoords = 0,
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| 114 | std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0)
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| 115 | {
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| 116 | enum { IsRowMajor = DynamicSparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
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| 117 | sparseMat.setZero();
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| 118 | sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
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| 119 | for(int j=0; j<sparseMat.outerSize(); j++)
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| 120 | {
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| 121 | sparseMat.startVec(j); // not needed for DynamicSparseMatrix
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| 122 | for(int i=0; i<sparseMat.innerSize(); i++)
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| 123 | {
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| 124 | int ai(i), aj(j);
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| 125 | if(IsRowMajor)
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| 126 | std::swap(ai,aj);
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| 127 | Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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| 128 | if ((flags&ForceNonZeroDiag) && (i==j))
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| 129 | {
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| 130 | v = internal::random<Scalar>()*Scalar(3.);
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| 131 | v = v*v + Scalar(5.);
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| 132 | }
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| 133 | if ((flags & MakeLowerTriangular) && aj>ai)
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| 134 | v = Scalar(0);
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| 135 | else if ((flags & MakeUpperTriangular) && aj<ai)
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| 136 | v = Scalar(0);
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| 137 |
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| 138 | if ((flags&ForceRealDiag) && (i==j))
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| 139 | v = numext::real(v);
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| 140 |
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| 141 | if (v!=Scalar(0))
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| 142 | {
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| 143 | sparseMat.insertBackByOuterInner(j,i) = v;
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| 144 | if (nonzeroCoords)
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| 145 | nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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| 146 | }
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| 147 | else if (zeroCoords)
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| 148 | {
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| 149 | zeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
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| 150 | }
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| 151 | refMat(ai,aj) = v;
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| 152 | }
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| 153 | }
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| 154 | sparseMat.finalize();
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| 155 | }
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| 156 |
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| 157 | template<typename Scalar,int Options,typename Index> void
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| 158 | initSparse(double density,
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| 159 | Matrix<Scalar,Dynamic,1>& refVec,
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| 160 | SparseVector<Scalar,Options,Index>& sparseVec,
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| 161 | std::vector<int>* zeroCoords = 0,
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| 162 | std::vector<int>* nonzeroCoords = 0)
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| 163 | {
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| 164 | sparseVec.reserve(int(refVec.size()*density));
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| 165 | sparseVec.setZero();
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| 166 | for(Index i=0; i<refVec.size(); i++)
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| 167 | {
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| 168 | Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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| 169 | if (v!=Scalar(0))
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| 170 | {
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| 171 | sparseVec.insertBack(i) = v;
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| 172 | if (nonzeroCoords)
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| 173 | nonzeroCoords->push_back(i);
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| 174 | }
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| 175 | else if (zeroCoords)
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| 176 | zeroCoords->push_back(i);
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| 177 | refVec[i] = v;
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| 178 | }
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| 179 | }
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| 180 |
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| 181 | template<typename Scalar,int Options,typename Index> void
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| 182 | initSparse(double density,
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| 183 | Matrix<Scalar,1,Dynamic>& refVec,
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| 184 | SparseVector<Scalar,Options,Index>& sparseVec,
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| 185 | std::vector<int>* zeroCoords = 0,
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| 186 | std::vector<int>* nonzeroCoords = 0)
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| 187 | {
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| 188 | sparseVec.reserve(int(refVec.size()*density));
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| 189 | sparseVec.setZero();
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| 190 | for(int i=0; i<refVec.size(); i++)
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| 191 | {
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| 192 | Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
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| 193 | if (v!=Scalar(0))
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| 194 | {
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| 195 | sparseVec.insertBack(i) = v;
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| 196 | if (nonzeroCoords)
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| 197 | nonzeroCoords->push_back(i);
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| 198 | }
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| 199 | else if (zeroCoords)
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| 200 | zeroCoords->push_back(i);
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| 201 | refVec[i] = v;
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| 202 | }
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| 203 | }
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| 204 |
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| 205 |
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| 206 | #include <unsupported/Eigen/SparseExtra>
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| 207 | #endif // EIGEN_TESTSPARSE_H
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