155 lines
4.2 KiB
C
155 lines
4.2 KiB
C
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_TESTSPARSE_H
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#include "main.h"
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#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC
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#include <tr1/unordered_map>
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#define EIGEN_UNORDERED_MAP_SUPPORT
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namespace std {
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using std::tr1::unordered_map;
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}
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#endif
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#ifdef EIGEN_GOOGLEHASH_SUPPORT
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#include <google/sparse_hash_map>
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#endif
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#include <Eigen/Cholesky>
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#include <Eigen/LU>
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#include <Eigen/Sparse>
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enum {
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ForceNonZeroDiag = 1,
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MakeLowerTriangular = 2,
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MakeUpperTriangular = 4,
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ForceRealDiag = 8
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};
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/* Initializes both a sparse and dense matrix with same random values,
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* and a ratio of \a density non zero entries.
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* \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
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* allowing to control the shape of the matrix.
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* \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
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* and zero coefficients respectively.
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*/
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template<typename Scalar> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,Dynamic>& refMat,
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SparseMatrix<Scalar>& sparseMat,
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int flags = 0,
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std::vector<Vector2i>* zeroCoords = 0,
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std::vector<Vector2i>* nonzeroCoords = 0)
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{
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sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
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for(int j=0; j<refMat.cols(); j++)
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{
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for(int i=0; i<refMat.rows(); i++)
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{
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Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
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if ((flags&ForceNonZeroDiag) && (i==j))
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{
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v = ei_random<Scalar>()*Scalar(3.);
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v = v*v + Scalar(5.);
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}
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if ((flags & MakeLowerTriangular) && j>i)
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v = Scalar(0);
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else if ((flags & MakeUpperTriangular) && j<i)
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v = Scalar(0);
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if ((flags&ForceRealDiag) && (i==j))
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v = ei_real(v);
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if (v!=Scalar(0))
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{
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sparseMat.fill(i,j) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(Vector2i(i,j));
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}
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else if (zeroCoords)
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{
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zeroCoords->push_back(Vector2i(i,j));
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}
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refMat(i,j) = v;
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}
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}
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sparseMat.endFill();
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}
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template<typename Scalar> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,Dynamic>& refMat,
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DynamicSparseMatrix<Scalar>& sparseMat,
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int flags = 0,
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std::vector<Vector2i>* zeroCoords = 0,
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std::vector<Vector2i>* nonzeroCoords = 0)
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{
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sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
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for(int j=0; j<refMat.cols(); j++)
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{
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for(int i=0; i<refMat.rows(); i++)
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{
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Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
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if ((flags&ForceNonZeroDiag) && (i==j))
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{
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v = ei_random<Scalar>()*Scalar(3.);
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v = v*v + Scalar(5.);
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}
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if ((flags & MakeLowerTriangular) && j>i)
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v = Scalar(0);
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else if ((flags & MakeUpperTriangular) && j<i)
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v = Scalar(0);
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if ((flags&ForceRealDiag) && (i==j))
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v = ei_real(v);
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if (v!=Scalar(0))
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{
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sparseMat.fill(i,j) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(Vector2i(i,j));
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}
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else if (zeroCoords)
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{
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zeroCoords->push_back(Vector2i(i,j));
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}
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refMat(i,j) = v;
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}
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}
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sparseMat.endFill();
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}
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template<typename Scalar> void
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initSparse(double density,
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Matrix<Scalar,Dynamic,1>& refVec,
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SparseVector<Scalar>& sparseVec,
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std::vector<int>* zeroCoords = 0,
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std::vector<int>* nonzeroCoords = 0)
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{
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sparseVec.reserve(int(refVec.size()*density));
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sparseVec.setZero();
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for(int i=0; i<refVec.size(); i++)
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{
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Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
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if (v!=Scalar(0))
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{
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sparseVec.fill(i) = v;
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if (nonzeroCoords)
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nonzeroCoords->push_back(i);
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}
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else if (zeroCoords)
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zeroCoords->push_back(i);
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refVec[i] = v;
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}
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}
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#endif // EIGEN_TESTSPARSE_H
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