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Diffstat (limited to 'unsupported/test/sparse_extra.cpp')
-rw-r--r-- | unsupported/test/sparse_extra.cpp | 153 |
1 files changed, 153 insertions, 0 deletions
diff --git a/unsupported/test/sparse_extra.cpp b/unsupported/test/sparse_extra.cpp new file mode 100644 index 000000000..fa6dc50f5 --- /dev/null +++ b/unsupported/test/sparse_extra.cpp @@ -0,0 +1,153 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#include "sparse.h" +#include <Eigen/SparseExtra> + +template<typename SetterType,typename DenseType, typename Scalar, int Options> +bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords) +{ + typedef SparseMatrix<Scalar,Options> SparseType; + { + sm.setZero(); + SetterType w(sm); + std::vector<Vector2i> remaining = nonzeroCoords; + while(!remaining.empty()) + { + int i = ei_random<int>(0,static_cast<int>(remaining.size())-1); + w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y()); + remaining[i] = remaining.back(); + remaining.pop_back(); + } + } + return sm.isApprox(ref); +} + +template<typename SetterType,typename DenseType, typename T> +bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords) +{ + sm.setZero(); + std::vector<Vector2i> remaining = nonzeroCoords; + while(!remaining.empty()) + { + int i = ei_random<int>(0,static_cast<int>(remaining.size())-1); + sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y()); + remaining[i] = remaining.back(); + remaining.pop_back(); + } + return sm.isApprox(ref); +} + +template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& ref) +{ + const int rows = ref.rows(); + const int cols = ref.cols(); + typedef typename SparseMatrixType::Scalar Scalar; + enum { Flags = SparseMatrixType::Flags }; + + double density = std::max(8./(rows*cols), 0.01); + typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; + typedef Matrix<Scalar,Dynamic,1> DenseVector; + Scalar eps = 1e-6; + + SparseMatrixType m(rows, cols); + DenseMatrix refMat = DenseMatrix::Zero(rows, cols); + DenseVector vec1 = DenseVector::Random(rows); + + std::vector<Vector2i> zeroCoords; + std::vector<Vector2i> nonzeroCoords; + initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords); + + if (zeroCoords.size()==0 || nonzeroCoords.size()==0) + return; + + // test coeff and coeffRef + for (int i=0; i<(int)zeroCoords.size(); ++i) + { + VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps ); + if(ei_is_same_type<SparseMatrixType,SparseMatrix<Scalar,Flags> >::ret) + VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 ); + } + VERIFY_IS_APPROX(m, refMat); + + m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5); + refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5); + + VERIFY_IS_APPROX(m, refMat); + + // random setter +// { +// m.setZero(); +// VERIFY_IS_NOT_APPROX(m, refMat); +// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m); +// std::vector<Vector2i> remaining = nonzeroCoords; +// while(!remaining.empty()) +// { +// int i = ei_random<int>(0,remaining.size()-1); +// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y()); +// remaining[i] = remaining.back(); +// remaining.pop_back(); +// } +// } +// VERIFY_IS_APPROX(m, refMat); + + VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) )); + #ifdef EIGEN_UNORDERED_MAP_SUPPORT + VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) )); + #endif + #ifdef _DENSE_HASH_MAP_H_ + VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) )); + #endif + #ifdef _SPARSE_HASH_MAP_H_ + VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) )); + #endif + + + // test RandomSetter + /*{ + SparseMatrixType m1(rows,cols), m2(rows,cols); + DenseMatrix refM1 = DenseMatrix::Zero(rows, rows); + initSparse<Scalar>(density, refM1, m1); + { + Eigen::RandomSetter<SparseMatrixType > setter(m2); + for (int j=0; j<m1.outerSize(); ++j) + for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i) + setter(i.index(), j) = i.value(); + } + VERIFY_IS_APPROX(m1, m2); + }*/ + + +} + +void test_sparse_extra() +{ + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(8, 8)) ); + CALL_SUBTEST_2( sparse_extra(SparseMatrix<std::complex<double> >(16, 16)) ); + CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(33, 33)) ); + + CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix<double>(8, 8)) ); + } +} |