| // This file is part of Eigen, a lightweight C++ template library | 
 | // for linear algebra. | 
 | // | 
 | // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> | 
 | // | 
 | // This Source Code Form is subject to the terms of the Mozilla | 
 | // Public License v. 2.0. If a copy of the MPL was not distributed | 
 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
 |  | 
 | #ifndef EIGEN_TESTSPARSE_H | 
 | #define EIGEN_TESTSPARSE_H | 
 |  | 
 | #define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET | 
 |  | 
 | #include "main.h" | 
 |  | 
 | #ifdef min | 
 | #undef min | 
 | #endif | 
 |  | 
 | #ifdef max | 
 | #undef max | 
 | #endif | 
 |  | 
 | #include <unordered_map> | 
 | #define EIGEN_UNORDERED_MAP_SUPPORT | 
 |  | 
 | #include <Eigen/Cholesky> | 
 | #include <Eigen/LU> | 
 | #include <Eigen/Sparse> | 
 |  | 
 | enum { | 
 |   ForceNonZeroDiag = 1, | 
 |   MakeLowerTriangular = 2, | 
 |   MakeUpperTriangular = 4, | 
 |   ForceRealDiag = 8 | 
 | }; | 
 |  | 
 | /* Initializes both a sparse and dense matrix with same random values, | 
 |  * and a ratio of \a density non zero entries. | 
 |  * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular | 
 |  *        allowing to control the shape of the matrix. | 
 |  * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero, | 
 |  *        and zero coefficients respectively. | 
 |  */ | 
 | template<typename Scalar,int Opt1,int Opt2,typename StorageIndex> void | 
 | initSparse(double density, | 
 |            Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat, | 
 |            SparseMatrix<Scalar,Opt2,StorageIndex>& sparseMat, | 
 |            int flags = 0, | 
 |            std::vector<Matrix<StorageIndex,2,1> >* zeroCoords = 0, | 
 |            std::vector<Matrix<StorageIndex,2,1> >* nonzeroCoords = 0) | 
 | { | 
 |   enum { IsRowMajor = SparseMatrix<Scalar,Opt2,StorageIndex>::IsRowMajor }; | 
 |   sparseMat.setZero(); | 
 |   //sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); | 
 |   sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows())))); | 
 |  | 
 |   Index insert_count = 0; | 
 |   for(Index j=0; j<sparseMat.outerSize(); j++) | 
 |   { | 
 |     //sparseMat.startVec(j); | 
 |     for(Index i=0; i<sparseMat.innerSize(); i++) | 
 |     { | 
 |       Index ai(i), aj(j); | 
 |       if(IsRowMajor) | 
 |         std::swap(ai,aj); | 
 |       Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0); | 
 |       if ((flags&ForceNonZeroDiag) && (i==j)) | 
 |       { | 
 |         // FIXME: the following is too conservative | 
 |         v = internal::random<Scalar>()*Scalar(3.); | 
 |         v = v*v; | 
 |         if(numext::real(v)>0) v += Scalar(5); | 
 |         else                  v -= Scalar(5); | 
 |       } | 
 |       if ((flags & MakeLowerTriangular) && aj>ai) | 
 |         v = Scalar(0); | 
 |       else if ((flags & MakeUpperTriangular) && aj<ai) | 
 |         v = Scalar(0); | 
 |  | 
 |       if ((flags&ForceRealDiag) && (i==j)) | 
 |         v = numext::real(v); | 
 |  | 
 |       if (v!=Scalar(0)) | 
 |       { | 
 |         //sparseMat.insertBackByOuterInner(j,i) = v; | 
 |         sparseMat.insertByOuterInner(j,i) = v; | 
 |         ++insert_count; | 
 |         if (nonzeroCoords) | 
 |           nonzeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj)); | 
 |       } | 
 |       else if (zeroCoords) | 
 |       { | 
 |         zeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj)); | 
 |       } | 
 |       refMat(ai,aj) = v; | 
 |  | 
 |       // make sure we only insert as many as the sparse matrix supports | 
 |       if(insert_count == NumTraits<StorageIndex>::highest()) return; | 
 |     } | 
 |   } | 
 |   //sparseMat.finalize(); | 
 | } | 
 |  | 
 | template<typename Scalar,int Options,typename Index> void | 
 | initSparse(double density, | 
 |            Matrix<Scalar,Dynamic,1>& refVec, | 
 |            SparseVector<Scalar,Options,Index>& sparseVec, | 
 |            std::vector<int>* zeroCoords = 0, | 
 |            std::vector<int>* nonzeroCoords = 0) | 
 | { | 
 |   sparseVec.reserve(int(refVec.size()*density)); | 
 |   sparseVec.setZero(); | 
 |   for(int i=0; i<refVec.size(); i++) | 
 |   { | 
 |     Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0); | 
 |     if (v!=Scalar(0)) | 
 |     { | 
 |       sparseVec.insertBack(i) = v; | 
 |       if (nonzeroCoords) | 
 |         nonzeroCoords->push_back(i); | 
 |     } | 
 |     else if (zeroCoords) | 
 |         zeroCoords->push_back(i); | 
 |     refVec[i] = v; | 
 |   } | 
 | } | 
 |  | 
 | template<typename Scalar,int Options,typename Index> void | 
 | initSparse(double density, | 
 |            Matrix<Scalar,1,Dynamic>& refVec, | 
 |            SparseVector<Scalar,Options,Index>& sparseVec, | 
 |            std::vector<int>* zeroCoords = 0, | 
 |            std::vector<int>* nonzeroCoords = 0) | 
 | { | 
 |   sparseVec.reserve(int(refVec.size()*density)); | 
 |   sparseVec.setZero(); | 
 |   for(int i=0; i<refVec.size(); i++) | 
 |   { | 
 |     Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0); | 
 |     if (v!=Scalar(0)) | 
 |     { | 
 |       sparseVec.insertBack(i) = v; | 
 |       if (nonzeroCoords) | 
 |         nonzeroCoords->push_back(i); | 
 |     } | 
 |     else if (zeroCoords) | 
 |         zeroCoords->push_back(i); | 
 |     refVec[i] = v; | 
 |   } | 
 | } | 
 |  | 
 |  | 
 | #include <unsupported/Eigen/SparseExtra> | 
 | #endif // EIGEN_TESTSPARSE_H |