diff options
Diffstat (limited to 'test/sparse_basic.cpp')
| -rw-r--r-- | test/sparse_basic.cpp | 126 |
1 files changed, 99 insertions, 27 deletions
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp index 384985028..9453111b7 100644 --- a/test/sparse_basic.cpp +++ b/test/sparse_basic.cpp @@ -9,9 +9,16 @@ // 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/. +#ifndef EIGEN_SPARSE_TEST_INCLUDED_FROM_SPARSE_EXTRA static long g_realloc_count = 0; #define EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN g_realloc_count++; +static long g_dense_op_sparse_count = 0; +#define EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN g_dense_op_sparse_count++; +#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN g_dense_op_sparse_count+=10; +#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN g_dense_op_sparse_count+=20; +#endif + #include "sparse.h" template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref) @@ -194,6 +201,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re VERIFY_IS_APPROX(refM4.cwiseProduct(m3), refM4.cwiseProduct(refM3)); // VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4); + // mixed sparse-dense VERIFY_IS_APPROX(refM4 + m3, refM4 + refM3); VERIFY_IS_APPROX(m3 + refM4, refM3 + refM4); VERIFY_IS_APPROX(refM4 - m3, refM4 - refM3); @@ -222,14 +230,34 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re VERIFY_IS_APPROX(m1+=m2, refM1+=refM2); VERIFY_IS_APPROX(m1-=m2, refM1-=refM2); + refM3 = refM1; + + VERIFY_IS_APPROX(refM1+=m2, refM3+=refM2); + VERIFY_IS_APPROX(refM1-=m2, refM3-=refM2); + + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1 =m2+refM4, refM3 =refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,10); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1+=m2+refM4, refM3+=refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1-=m2+refM4, refM3-=refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1 =refM4+m2, refM3 =refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1+=refM4+m2, refM3+=refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1-=refM4+m2, refM3-=refM2+refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1 =m2-refM4, refM3 =refM2-refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,20); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1+=m2-refM4, refM3+=refM2-refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1-=m2-refM4, refM3-=refM2-refM4); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1 =refM4-m2, refM3 =refM4-refM2); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1+=refM4-m2, refM3+=refM4-refM2); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + g_dense_op_sparse_count=0; VERIFY_IS_APPROX(refM1-=refM4-m2, refM3-=refM4-refM2); VERIFY_IS_EQUAL(g_dense_op_sparse_count,1); + refM3 = m3; + if (rows>=2 && cols>=2) { VERIFY_RAISES_ASSERT( m1 += m1.innerVector(0) ); VERIFY_RAISES_ASSERT( m1 -= m1.innerVector(0) ); VERIFY_RAISES_ASSERT( refM1 -= m1.innerVector(0) ); VERIFY_RAISES_ASSERT( refM1 += m1.innerVector(0) ); - m1 = m4; refM1 = refM4; } + m1 = m4; refM1 = refM4; // test aliasing VERIFY_IS_APPROX((m1 = -m1), (refM1 = -refM1)); @@ -385,7 +413,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re m.setFromTriplets(triplets.begin(), triplets.end(), std::multiplies<Scalar>()); VERIFY_IS_APPROX(m, refMat_prod); -#if (defined(__cplusplus) && __cplusplus >= 201103L) +#if (EIGEN_COMP_CXXVER >= 11) m.setFromTriplets(triplets.begin(), triplets.end(), [] (Scalar,Scalar b) { return b; }); VERIFY_IS_APPROX(m, refMat_last); #endif @@ -518,7 +546,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re { DenseVector d = DenseVector::Random(rows); DenseMatrix refMat2 = d.asDiagonal(); - SparseMatrixType m2(rows, rows); + SparseMatrixType m2; m2 = d.asDiagonal(); VERIFY_IS_APPROX(m2, refMat2); SparseMatrixType m3(d.asDiagonal()); @@ -526,6 +554,28 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re refMat2 += d.asDiagonal(); m2 += d.asDiagonal(); VERIFY_IS_APPROX(m2, refMat2); + m2.setZero(); m2 += d.asDiagonal(); + refMat2.setZero(); refMat2 += d.asDiagonal(); + VERIFY_IS_APPROX(m2, refMat2); + m2.setZero(); m2 -= d.asDiagonal(); + refMat2.setZero(); refMat2 -= d.asDiagonal(); + VERIFY_IS_APPROX(m2, refMat2); + + initSparse<Scalar>(density, refMat2, m2); + m2.makeCompressed(); + m2 += d.asDiagonal(); + refMat2 += d.asDiagonal(); + VERIFY_IS_APPROX(m2, refMat2); + + initSparse<Scalar>(density, refMat2, m2); + m2.makeCompressed(); + VectorXi res(rows); + for(Index i=0; i<rows; ++i) + res(i) = internal::random<int>(0,3); + m2.reserve(res); + m2 -= d.asDiagonal(); + refMat2 -= d.asDiagonal(); + VERIFY_IS_APPROX(m2, refMat2); } // test conservative resize @@ -537,30 +587,38 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re inc.push_back(std::pair<StorageIndex,StorageIndex>(3,2)); inc.push_back(std::pair<StorageIndex,StorageIndex>(3,0)); inc.push_back(std::pair<StorageIndex,StorageIndex>(0,3)); - + inc.push_back(std::pair<StorageIndex,StorageIndex>(0,-1)); + inc.push_back(std::pair<StorageIndex,StorageIndex>(-1,0)); + inc.push_back(std::pair<StorageIndex,StorageIndex>(-1,-1)); + for(size_t i = 0; i< inc.size(); i++) { StorageIndex incRows = inc[i].first; StorageIndex incCols = inc[i].second; SparseMatrixType m1(rows, cols); DenseMatrix refMat1 = DenseMatrix::Zero(rows, cols); initSparse<Scalar>(density, refMat1, m1); - + + SparseMatrixType m2 = m1; + m2.makeCompressed(); + m1.conservativeResize(rows+incRows, cols+incCols); + m2.conservativeResize(rows+incRows, cols+incCols); refMat1.conservativeResize(rows+incRows, cols+incCols); if (incRows > 0) refMat1.bottomRows(incRows).setZero(); if (incCols > 0) refMat1.rightCols(incCols).setZero(); - + VERIFY_IS_APPROX(m1, refMat1); - + VERIFY_IS_APPROX(m2, refMat1); + // Insert new values if (incRows > 0) m1.insert(m1.rows()-1, 0) = refMat1(refMat1.rows()-1, 0) = 1; if (incCols > 0) m1.insert(0, m1.cols()-1) = refMat1(0, refMat1.cols()-1) = 1; - + VERIFY_IS_APPROX(m1, refMat1); - - + + } } @@ -612,6 +670,14 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re iters[0] = IteratorType(m2,0); iters[1] = IteratorType(m2,m2.outerSize()-1); } + + // test reserve with empty rows/columns + { + SparseMatrixType m1(0,cols); + m1.reserve(ArrayXi::Constant(m1.outerSize(),1)); + SparseMatrixType m2(rows,0); + m2.reserve(ArrayXi::Constant(m2.outerSize(),1)); + } } @@ -622,7 +688,7 @@ void big_sparse_triplet(Index rows, Index cols, double density) { typedef Triplet<Scalar,Index> TripletType; std::vector<TripletType> triplets; double nelements = density * rows*cols; - VERIFY(nelements>=0 && nelements < NumTraits<StorageIndex>::highest()); + VERIFY(nelements>=0 && nelements < static_cast<double>(NumTraits<StorageIndex>::highest())); Index ntriplets = Index(nelements); triplets.reserve(ntriplets); Scalar sum = Scalar(0); @@ -630,7 +696,8 @@ void big_sparse_triplet(Index rows, Index cols, double density) { { Index r = internal::random<Index>(0,rows-1); Index c = internal::random<Index>(0,cols-1); - Scalar v = internal::random<Scalar>(); + // use positive values to prevent numerical cancellation errors in sum + Scalar v = numext::abs(internal::random<Scalar>()); triplets.push_back(TripletType(r,c,v)); sum += v; } @@ -640,9 +707,26 @@ void big_sparse_triplet(Index rows, Index cols, double density) { VERIFY_IS_APPROX(sum, m.sum()); } +template<int> +void bug1105() +{ + // Regression test for bug 1105 + int n = Eigen::internal::random<int>(200,600); + SparseMatrix<std::complex<double>,0, long> mat(n, n); + std::complex<double> val; + + for(int i=0; i<n; ++i) + { + mat.coeffRef(i, i%(n/10)) = val; + VERIFY(mat.data().allocatedSize()<20*n); + } +} + +#ifndef EIGEN_SPARSE_TEST_INCLUDED_FROM_SPARSE_EXTRA -void test_sparse_basic() +EIGEN_DECLARE_TEST(sparse_basic) { + g_dense_op_sparse_count = 0; // Suppresses compiler warning. for(int i = 0; i < g_repeat; i++) { int r = Eigen::internal::random<int>(1,200), c = Eigen::internal::random<int>(1,200); if(Eigen::internal::random<int>(0,4) == 0) { @@ -671,18 +755,6 @@ void test_sparse_basic() CALL_SUBTEST_3((big_sparse_triplet<SparseMatrix<float, RowMajor, int> >(10000, 10000, 0.125))); CALL_SUBTEST_4((big_sparse_triplet<SparseMatrix<double, ColMajor, long int> >(10000, 10000, 0.125))); - // Regression test for bug 1105 -#ifdef EIGEN_TEST_PART_7 - { - int n = Eigen::internal::random<int>(200,600); - SparseMatrix<std::complex<double>,0, long> mat(n, n); - std::complex<double> val; - - for(int i=0; i<n; ++i) - { - mat.coeffRef(i, i%(n/10)) = val; - VERIFY(mat.data().allocatedSize()<20*n); - } - } -#endif + CALL_SUBTEST_7( bug1105<0>() ); } +#endif |