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author | Stanislaw Halik <sthalik@misaki.pl> | 2017-03-25 14:17:07 +0100 |
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committer | Stanislaw Halik <sthalik@misaki.pl> | 2017-03-25 14:17:07 +0100 |
commit | 35f7829af10c61e33dd2e2a7a015058e11a11ea0 (patch) | |
tree | 7135010dcf8fd0a49f3020d52112709bcb883bd6 /eigen/test/sparse_vector.cpp | |
parent | 6e8724193e40a932faf9064b664b529e7301c578 (diff) |
update
Diffstat (limited to 'eigen/test/sparse_vector.cpp')
-rw-r--r-- | eigen/test/sparse_vector.cpp | 75 |
1 files changed, 64 insertions, 11 deletions
diff --git a/eigen/test/sparse_vector.cpp b/eigen/test/sparse_vector.cpp index 0c94768..b3e1dda 100644 --- a/eigen/test/sparse_vector.cpp +++ b/eigen/test/sparse_vector.cpp @@ -9,22 +9,22 @@ #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); + double densityVec = (std::max)(8./(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); 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); + refV2 = DenseVector::Random(rows), + refV3 = DenseVector::Random(rows); std::vector<int> zerocoords, nonzerocoords; initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords); @@ -52,6 +52,20 @@ template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) } } VERIFY_IS_APPROX(v1, refV1); + + // test coeffRef with reallocation + { + SparseVectorType v4(rows); + DenseVector v5 = DenseVector::Zero(rows); + for(int k=0; k<rows; ++k) + { + int i = internal::random<int>(0,rows-1); + Scalar v = internal::random<Scalar>(); + v4.coeffRef(i) += v; + v5.coeffRef(i) += v; + } + VERIFY_IS_APPROX(v4,v5); + } v1.coeffRef(nonzerocoords[0]) = Scalar(5); refV1.coeffRef(nonzerocoords[0]) = Scalar(5); @@ -71,9 +85,12 @@ template<typename Scalar,typename Index> void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2)); VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2)); + 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()); @@ -96,15 +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) )); } } |