// 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" #if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC && !defined(__clang__) #ifdef min #undef min #endif #ifdef max #undef max #endif #include <tr1/unordered_map> #define EIGEN_UNORDERED_MAP_SUPPORT namespace std { using std::tr1::unordered_map; } #endif #ifdef EIGEN_GOOGLEHASH_SUPPORT #include <google/sparse_hash_map> #endif #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())))); 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; 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; } } //sparseMat.finalize(); } template<typename Scalar,int Opt1,int Opt2,typename Index> void initSparse(double density, Matrix<Scalar,Dynamic,Dynamic, Opt1>& refMat, DynamicSparseMatrix<Scalar, Opt2, Index>& sparseMat, int flags = 0, std::vector<Matrix<Index,2,1> >* zeroCoords = 0, std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0) { enum { IsRowMajor = DynamicSparseMatrix<Scalar,Opt2,Index>::IsRowMajor }; sparseMat.setZero(); sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); for(int j=0; j<sparseMat.outerSize(); j++) { sparseMat.startVec(j); // not needed for DynamicSparseMatrix for(int i=0; i<sparseMat.innerSize(); i++) { int 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)) { v = internal::random<Scalar>()*Scalar(3.); v = v*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; if (nonzeroCoords) nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj)); } else if (zeroCoords) { zeroCoords->push_back(Matrix<Index,2,1> (ai,aj)); } refMat(ai,aj) = v; } } 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