diff options
author | Gael Guennebaud <g.gael@free.fr> | 2015-03-19 15:11:05 +0100 |
---|---|---|
committer | Gael Guennebaud <g.gael@free.fr> | 2015-03-19 15:11:05 +0100 |
commit | d7698c18b7801f041c36adffcdfaefc99140887f (patch) | |
tree | e1ae574d52a172f8c85082f1b24348f0db2e3c23 /test/sparse_basic.cpp | |
parent | f329d0908af35fd17bdc4dfeb87046dcaa6e6937 (diff) |
Split sparse_basic unit test
Diffstat (limited to 'test/sparse_basic.cpp')
-rw-r--r-- | test/sparse_basic.cpp | 204 |
1 files changed, 4 insertions, 200 deletions
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp index d929e1463..75f29a2b4 100644 --- a/test/sparse_basic.cpp +++ b/test/sparse_basic.cpp @@ -30,7 +30,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re double density = (std::max)(8./(rows*cols), 0.01); typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; typedef Matrix<Scalar,Dynamic,1> DenseVector; - typedef Matrix<Scalar,1,Dynamic> RowDenseVector; Scalar eps = 1e-6; Scalar s1 = internal::random<Scalar>(); @@ -59,77 +58,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re VERIFY_IS_APPROX(m, refMat); - // test InnerIterators and Block expressions - for (int t=0; t<10; ++t) - { - Index j = internal::random<Index>(0,cols-2); - Index i = internal::random<Index>(0,rows-2); - Index w = internal::random<Index>(1,cols-j); - Index h = internal::random<Index>(1,rows-i); - - VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w)); - for(Index c=0; c<w; c++) - { - VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c)); - for(Index r=0; r<h; r++) - { - VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r)); - VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c)); - } - } - for(Index r=0; r<h; r++) - { - VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r)); - for(Index c=0; c<w; c++) - { - VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c)); - VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c)); - } - } - - VERIFY_IS_APPROX(m.middleCols(j,w), refMat.middleCols(j,w)); - VERIFY_IS_APPROX(m.middleRows(i,h), refMat.middleRows(i,h)); - for(Index r=0; r<h; r++) - { - VERIFY_IS_APPROX(m.middleCols(j,w).row(r), refMat.middleCols(j,w).row(r)); - VERIFY_IS_APPROX(m.middleRows(i,h).row(r), refMat.middleRows(i,h).row(r)); - for(Index c=0; c<w; c++) - { - VERIFY_IS_APPROX(m.col(c).coeff(r), refMat.col(c).coeff(r)); - VERIFY_IS_APPROX(m.row(r).coeff(c), refMat.row(r).coeff(c)); - - VERIFY_IS_APPROX(m.middleCols(j,w).coeff(r,c), refMat.middleCols(j,w).coeff(r,c)); - VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c)); - if(m.middleCols(j,w).coeff(r,c) != Scalar(0)) - { - VERIFY_IS_APPROX(m.middleCols(j,w).coeffRef(r,c), refMat.middleCols(j,w).coeff(r,c)); - } - if(m.middleRows(i,h).coeff(r,c) != Scalar(0)) - { - VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c)); - } - } - } - for(Index c=0; c<w; c++) - { - VERIFY_IS_APPROX(m.middleCols(j,w).col(c), refMat.middleCols(j,w).col(c)); - VERIFY_IS_APPROX(m.middleRows(i,h).col(c), refMat.middleRows(i,h).col(c)); - } - } - - for(Index c=0; c<cols; c++) - { - VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c)); - VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c)); - } - - for(Index r=0; r<rows; r++) - { - VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r)); - VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r)); - } - - // test assertion VERIFY_RAISES_ASSERT( m.coeffRef(-1,1) = 0 ); VERIFY_RAISES_ASSERT( m.coeffRef(0,m.cols()) = 0 ); @@ -214,82 +142,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re VERIFY_IS_APPROX(m2,m1); } - // test innerVector() - { - DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols); - SparseMatrixType m2(rows, cols); - initSparse<Scalar>(density, refMat2, m2); - Index j0 = internal::random<Index>(0,outer-1); - Index j1 = internal::random<Index>(0,outer-1); - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0)); - else - VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0)); - - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.row(j0)+refMat2.row(j1)); - else - VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1)); - - SparseMatrixType m3(rows,cols); - m3.reserve(VectorXi::Constant(outer,int(inner/2))); - for(Index j=0; j<outer; ++j) - for(Index k=0; k<(std::min)(j,inner); ++k) - m3.insertByOuterInner(j,k) = k+1; - for(Index j=0; j<(std::min)(outer, inner); ++j) - { - VERIFY(j==numext::real(m3.innerVector(j).nonZeros())); - if(j>0) - VERIFY(j==numext::real(m3.innerVector(j).lastCoeff())); - } - m3.makeCompressed(); - for(Index j=0; j<(std::min)(outer, inner); ++j) - { - VERIFY(j==numext::real(m3.innerVector(j).nonZeros())); - if(j>0) - VERIFY(j==numext::real(m3.innerVector(j).lastCoeff())); - } - - VERIFY(m3.innerVector(j0).nonZeros() == m3.transpose().innerVector(j0).nonZeros()); - -// m2.innerVector(j0) = 2*m2.innerVector(j1); -// refMat2.col(j0) = 2*refMat2.col(j1); -// VERIFY_IS_APPROX(m2, refMat2); - } - - // test innerVectors() - { - DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols); - SparseMatrixType m2(rows, cols); - initSparse<Scalar>(density, refMat2, m2); - if(internal::random<float>(0,1)>0.5) m2.makeCompressed(); - Index j0 = internal::random<Index>(0,outer-2); - Index j1 = internal::random<Index>(0,outer-2); - Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1)); - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols)); - else - VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0)); - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), - refMat2.middleRows(j0,n0)+refMat2.middleRows(j1,n0)); - else - VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), - refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0)); - - VERIFY_IS_APPROX(m2, refMat2); - - VERIFY(m2.innerVectors(j0,n0).nonZeros() == m2.transpose().innerVectors(j0,n0).nonZeros()); - - m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0); - if(SparseMatrixType::IsRowMajor) - refMat2.middleRows(j0,n0) = (refMat2.middleRows(j0,n0) + refMat2.middleRows(j1,n0)).eval(); - else - refMat2.middleCols(j0,n0) = (refMat2.middleCols(j0,n0) + refMat2.middleCols(j1,n0)).eval(); - - VERIFY_IS_APPROX(m2, refMat2); - } - // test basic computations { DenseMatrix refM1 = DenseMatrix::Zero(rows, cols); @@ -360,54 +212,6 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re VERIFY(m2.isApprox(m3)); } - - - // test generic blocks - { - DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols); - SparseMatrixType m2(rows, cols); - initSparse<Scalar>(density, refMat2, m2); - Index j0 = internal::random<Index>(0,outer-2); - Index j1 = internal::random<Index>(0,outer-2); - Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1)); - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols)); - else - VERIFY_IS_APPROX(m2.block(0,j0,rows,n0), refMat2.block(0,j0,rows,n0)); - - if(SparseMatrixType::IsRowMajor) - VERIFY_IS_APPROX(m2.block(j0,0,n0,cols)+m2.block(j1,0,n0,cols), - refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols)); - else - VERIFY_IS_APPROX(m2.block(0,j0,rows,n0)+m2.block(0,j1,rows,n0), - refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0)); - - Index i = internal::random<Index>(0,m2.outerSize()-1); - if(SparseMatrixType::IsRowMajor) { - m2.innerVector(i) = m2.innerVector(i) * s1; - refMat2.row(i) = refMat2.row(i) * s1; - VERIFY_IS_APPROX(m2,refMat2); - } else { - m2.innerVector(i) = m2.innerVector(i) * s1; - refMat2.col(i) = refMat2.col(i) * s1; - VERIFY_IS_APPROX(m2,refMat2); - } - - Index r0 = internal::random<Index>(0,rows-2); - Index c0 = internal::random<Index>(0,cols-2); - Index r1 = internal::random<Index>(1,rows-r0); - Index c1 = internal::random<Index>(1,cols-c0); - - VERIFY_IS_APPROX(DenseVector(m2.col(c0)), refMat2.col(c0)); - VERIFY_IS_APPROX(m2.col(c0), refMat2.col(c0)); - - VERIFY_IS_APPROX(RowDenseVector(m2.row(r0)), refMat2.row(r0)); - VERIFY_IS_APPROX(m2.row(r0), refMat2.row(r0)); - - VERIFY_IS_APPROX(m2.block(r0,c0,r1,c1), refMat2.block(r0,c0,r1,c1)); - VERIFY_IS_APPROX((2*m2).block(r0,c0,r1,c1), (2*refMat2).block(r0,c0,r1,c1)); - } - // test prune { SparseMatrixType m2(rows, cols); @@ -646,8 +450,8 @@ void test_sparse_basic() CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(r, c)) )); CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(r, c)) )); CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(r, c)) )); - CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(r, c)) )); - CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(r, c)) )); + CALL_SUBTEST_5(( sparse_basic(SparseMatrix<double,ColMajor,long int>(r, c)) )); + CALL_SUBTEST_5(( sparse_basic(SparseMatrix<double,RowMajor,long int>(r, c)) )); r = Eigen::internal::random<int>(1,100); c = Eigen::internal::random<int>(1,100); @@ -655,8 +459,8 @@ void test_sparse_basic() r = c; // check square matrices in 25% of tries } - CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) )); - CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) )); + CALL_SUBTEST_6(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) )); + CALL_SUBTEST_6(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) )); } // Regression test for bug 900: (manually insert higher values here, if you have enough RAM): |