| // 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_HAS_CXX11 | |
| #ifdef min | |
| #undef min | |
| #endif | |
| #ifdef max | |
| #undef max | |
| #endif | |
| #include <unordered_map> | |
| #define EIGEN_UNORDERED_MAP_SUPPORT | |
| #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 |