// This file is part of Eigen, a lightweight C++ template library // for linear algebra. Eigen itself is part of the KDE project. // // Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> // // 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 #include "main.h" #if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC #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> void initSparse(double density, Matrix<Scalar,Dynamic,Dynamic>& refMat, SparseMatrix<Scalar>& sparseMat, int flags = 0, std::vector<Vector2i>* zeroCoords = 0, std::vector<Vector2i>* nonzeroCoords = 0) { sparseMat.startFill(int(refMat.rows()*refMat.cols()*density)); for(int j=0; j<refMat.cols(); j++) { for(int i=0; i<refMat.rows(); i++) { Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = ei_random<Scalar>()*Scalar(3.); v = v*v + Scalar(5.); } if ((flags & MakeLowerTriangular) && j>i) v = Scalar(0); else if ((flags & MakeUpperTriangular) && j<i) v = Scalar(0); if ((flags&ForceRealDiag) && (i==j)) v = ei_real(v); if (v!=Scalar(0)) { sparseMat.fill(i,j) = v; if (nonzeroCoords) nonzeroCoords->push_back(Vector2i(i,j)); } else if (zeroCoords) { zeroCoords->push_back(Vector2i(i,j)); } refMat(i,j) = v; } } sparseMat.endFill(); } template<typename Scalar> void initSparse(double density, Matrix<Scalar,Dynamic,Dynamic>& refMat, DynamicSparseMatrix<Scalar>& sparseMat, int flags = 0, std::vector<Vector2i>* zeroCoords = 0, std::vector<Vector2i>* nonzeroCoords = 0) { sparseMat.startFill(int(refMat.rows()*refMat.cols()*density)); for(int j=0; j<refMat.cols(); j++) { for(int i=0; i<refMat.rows(); i++) { Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = ei_random<Scalar>()*Scalar(3.); v = v*v + Scalar(5.); } if ((flags & MakeLowerTriangular) && j>i) v = Scalar(0); else if ((flags & MakeUpperTriangular) && j<i) v = Scalar(0); if ((flags&ForceRealDiag) && (i==j)) v = ei_real(v); if (v!=Scalar(0)) { sparseMat.fill(i,j) = v; if (nonzeroCoords) nonzeroCoords->push_back(Vector2i(i,j)); } else if (zeroCoords) { zeroCoords->push_back(Vector2i(i,j)); } refMat(i,j) = v; } } sparseMat.endFill(); } template<typename Scalar> void initSparse(double density, Matrix<Scalar,Dynamic,1>& refVec, SparseVector<Scalar>& 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 = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0); if (v!=Scalar(0)) { sparseVec.fill(i) = v; if (nonzeroCoords) nonzeroCoords->push_back(i); } else if (zeroCoords) zeroCoords->push_back(i); refVec[i] = v; } } #endif // EIGEN_TESTSPARSE_H