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Diffstat (limited to 'eigen/test/sparse_vector.cpp')
-rw-r--r-- | eigen/test/sparse_vector.cpp | 110 |
1 files changed, 110 insertions, 0 deletions
diff --git a/eigen/test/sparse_vector.cpp b/eigen/test/sparse_vector.cpp new file mode 100644 index 0000000..0c94768 --- /dev/null +++ b/eigen/test/sparse_vector.cpp @@ -0,0 +1,110 @@ +// 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/. + +#include "sparse.h" + +template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) +{ + double densityMat = (std::max)(8./(rows*cols), 0.01); + double densityVec = (std::max)(8./float(rows), 0.1); + typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; + typedef Matrix<Scalar,Dynamic,1> DenseVector; + typedef SparseVector<Scalar,0,Index> SparseVectorType; + typedef SparseMatrix<Scalar,0,Index> SparseMatrixType; + Scalar eps = 1e-6; + + SparseMatrixType m1(rows,rows); + SparseVectorType v1(rows), v2(rows), v3(rows); + DenseMatrix refM1 = DenseMatrix::Zero(rows, rows); + DenseVector refV1 = DenseVector::Random(rows), + refV2 = DenseVector::Random(rows), + refV3 = DenseVector::Random(rows); + + std::vector<int> zerocoords, nonzerocoords; + initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords); + initSparse<Scalar>(densityMat, refM1, m1); + + initSparse<Scalar>(densityVec, refV2, v2); + initSparse<Scalar>(densityVec, refV3, v3); + + Scalar s1 = internal::random<Scalar>(); + + // test coeff and coeffRef + for (unsigned int i=0; i<zerocoords.size(); ++i) + { + VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps ); + //VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 ); + } + { + VERIFY(int(nonzerocoords.size()) == v1.nonZeros()); + int j=0; + for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j) + { + VERIFY(nonzerocoords[j]==it.index()); + VERIFY(it.value()==v1.coeff(it.index())); + VERIFY(it.value()==refV1.coeff(it.index())); + } + } + VERIFY_IS_APPROX(v1, refV1); + + v1.coeffRef(nonzerocoords[0]) = Scalar(5); + refV1.coeffRef(nonzerocoords[0]) = Scalar(5); + VERIFY_IS_APPROX(v1, refV1); + + VERIFY_IS_APPROX(v1+v2, refV1+refV2); + VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3); + + VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2); + + VERIFY_IS_APPROX(v1*=s1, refV1*=s1); + VERIFY_IS_APPROX(v1/=s1, refV1/=s1); + + VERIFY_IS_APPROX(v1+=v2, refV1+=refV2); + VERIFY_IS_APPROX(v1-=v2, refV1-=refV2); + + VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2)); + VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2)); + + VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2)); + int i = internal::random<int>(0,rows-1); + VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i))); + + + VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm()); + + VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm()); + + // test aliasing + VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1)); + VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval())); + VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1)); + + // sparse matrix to sparse vector + SparseMatrixType mv1; + VERIFY_IS_APPROX((mv1=v1),v1); + VERIFY_IS_APPROX(mv1,(v1=mv1)); + VERIFY_IS_APPROX(mv1,(v1=mv1.transpose())); + + // check copy to dense vector with transpose + refV3.resize(0); + VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); + VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); + +} + +void test_sparse_vector() +{ + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) )); + CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(16, 16) )); + CALL_SUBTEST_1(( sparse_vector<double,long int>(299, 535) )); + CALL_SUBTEST_1(( sparse_vector<double,short>(299, 535) )); + } +} + |