diff options
author | Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-04-11 17:20:17 -0700 |
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committer | Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-04-11 17:20:17 -0700 |
commit | d6e596174d09446236b3f398d8ec39148c638ed9 (patch) | |
tree | ccb4116b05dc11d7931bac0129fd1394abe1e0b0 /test/sparse_vector.cpp | |
parent | 3ca1ae2bb761d7738bcdad885639f422a6b7c914 (diff) | |
parent | 833efb39bfe4957934982112fe435ab30a0c3b4f (diff) |
Pull latest updates from upstream
Diffstat (limited to 'test/sparse_vector.cpp')
-rw-r--r-- | test/sparse_vector.cpp | 54 |
1 files changed, 46 insertions, 8 deletions
diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp index d3975b99b..d95f301d5 100644 --- a/test/sparse_vector.cpp +++ b/test/sparse_vector.cpp @@ -9,14 +9,14 @@ #include "sparse.h" -template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) +template<typename Scalar,typename StorageIndex> 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; + typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType; + typedef SparseMatrix<Scalar,0,StorageIndex> SparseMatrixType; Scalar eps = 1e-6; SparseMatrixType m1(rows,rows); @@ -87,8 +87,10 @@ template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(m1*v2, refM1*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))); + { + 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()); @@ -111,15 +113,51 @@ template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); + // test conservative resize + { + std::vector<StorageIndex> inc; + if(rows > 3) + inc.push_back(-3); + inc.push_back(0); + inc.push_back(3); + inc.push_back(1); + inc.push_back(10); + + for(std::size_t i = 0; i< inc.size(); i++) { + StorageIndex incRows = inc[i]; + SparseVectorType vec1(rows); + DenseVector refVec1 = DenseVector::Zero(rows); + initSparse<Scalar>(densityVec, refVec1, vec1); + + vec1.conservativeResize(rows+incRows); + refVec1.conservativeResize(rows+incRows); + if (incRows > 0) refVec1.tail(incRows).setZero(); + + VERIFY_IS_APPROX(vec1, refVec1); + + // Insert new values + if (incRows > 0) + vec1.insert(vec1.rows()-1) = refVec1(refVec1.rows()-1) = 1; + + VERIFY_IS_APPROX(vec1, refVec1); + } + } + } void test_sparse_vector() { for(int i = 0; i < g_repeat; i++) { + int r = Eigen::internal::random<int>(1,500), c = Eigen::internal::random<int>(1,500); + if(Eigen::internal::random<int>(0,4) == 0) { + r = c; // check square matrices in 25% of tries + } + EIGEN_UNUSED_VARIABLE(r+c); + 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) )); + CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(r, c) )); + CALL_SUBTEST_1(( sparse_vector<double,long int>(r, c) )); + CALL_SUBTEST_1(( sparse_vector<double,short>(r, c) )); } } |