diff options
author | Gael Guennebaud <g.gael@free.fr> | 2011-08-19 14:18:05 +0200 |
---|---|---|
committer | Gael Guennebaud <g.gael@free.fr> | 2011-08-19 14:18:05 +0200 |
commit | 42e2578ef9fcbb62ad6e07933ccf531f6f7cd1b3 (patch) | |
tree | 90cef174284cad35f0d13d4b991db83335554caf /test | |
parent | 5734ee6df42991e59609ffd26aaeb3c7aacd61e2 (diff) |
the min/max macros to detect unprotected min/max were undefined by some std header,
so let's declare them after and do the respective fixes ;)
Diffstat (limited to 'test')
-rw-r--r-- | test/householder.cpp | 2 | ||||
-rw-r--r-- | test/jacobisvd.cpp | 2 | ||||
-rw-r--r-- | test/lu.cpp | 6 | ||||
-rw-r--r-- | test/main.h | 12 | ||||
-rw-r--r-- | test/nullary.cpp | 2 | ||||
-rw-r--r-- | test/packetmath.cpp | 10 | ||||
-rw-r--r-- | test/prec_inverse_4x4.cpp | 2 | ||||
-rw-r--r-- | test/product.h | 10 | ||||
-rw-r--r-- | test/qr_colpivoting.cpp | 4 | ||||
-rw-r--r-- | test/qr_fullpivoting.cpp | 2 | ||||
-rw-r--r-- | test/redux.cpp | 18 | ||||
-rw-r--r-- | test/sparse.h | 9 | ||||
-rw-r--r-- | test/sparse_basic.cpp | 4 | ||||
-rw-r--r-- | test/sparse_product.cpp | 2 | ||||
-rw-r--r-- | test/sparse_solvers.cpp | 2 | ||||
-rw-r--r-- | test/sparse_vector.cpp | 4 | ||||
-rw-r--r-- | test/stable_norm.cpp | 4 | ||||
-rw-r--r-- | test/triangular.cpp | 2 |
18 files changed, 56 insertions, 41 deletions
diff --git a/test/householder.cpp b/test/householder.cpp index e0aa40733..6f6f317ea 100644 --- a/test/householder.cpp +++ b/test/householder.cpp @@ -48,7 +48,7 @@ template<typename MatrixType> void householder(const MatrixType& m) typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, Dynamic> VBlockMatrixType; typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::RowsAtCompileTime> TMatrixType; - Matrix<Scalar, EIGEN_SIZE_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp(std::max(rows,cols)); + Matrix<Scalar, EIGEN_SIZE_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp((std::max)(rows,cols)); Scalar* tmp = &_tmp.coeffRef(0,0); Scalar beta; diff --git a/test/jacobisvd.cpp b/test/jacobisvd.cpp index 92f07961b..14c965133 100644 --- a/test/jacobisvd.cpp +++ b/test/jacobisvd.cpp @@ -66,7 +66,7 @@ void jacobisvd_compare_to_full(const MatrixType& m, typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols(); - Index diagSize = std::min(rows, cols); + Index diagSize = (std::min)(rows, cols); JacobiSVD<MatrixType, QRPreconditioner> svd(m, computationOptions); diff --git a/test/lu.cpp b/test/lu.cpp index 46512405e..253f68542 100644 --- a/test/lu.cpp +++ b/test/lu.cpp @@ -64,7 +64,7 @@ template<typename MatrixType> void lu_non_invertible() typedef Matrix<typename MatrixType::Scalar, RowsAtCompileTime, RowsAtCompileTime> RMatrixType; - Index rank = internal::random<Index>(1, std::min(rows, cols)-1); + Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); // The image of the zero matrix should consist of a single (zero) column vector VERIFY((MatrixType::Zero(rows,cols).fullPivLu().image(MatrixType::Zero(rows,cols)).cols() == 1)); @@ -84,8 +84,8 @@ template<typename MatrixType> void lu_non_invertible() MatrixType u(rows,cols); u = lu.matrixLU().template triangularView<Upper>(); RMatrixType l = RMatrixType::Identity(rows,rows); - l.block(0,0,rows,std::min(rows,cols)).template triangularView<StrictlyLower>() - = lu.matrixLU().block(0,0,rows,std::min(rows,cols)); + l.block(0,0,rows,(std::min)(rows,cols)).template triangularView<StrictlyLower>() + = lu.matrixLU().block(0,0,rows,(std::min)(rows,cols)); VERIFY_IS_APPROX(lu.permutationP() * m1 * lu.permutationQ(), l*u); diff --git a/test/main.h b/test/main.h index 99049223c..2068713b3 100644 --- a/test/main.h +++ b/test/main.h @@ -23,9 +23,6 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see <http://www.gnu.org/licenses/>. -#define min(A,B) please_protect_your_min_with_parentheses -#define max(A,B) please_protect_your_max_with_parentheses - #include <cstdlib> #include <cerrno> #include <ctime> @@ -33,6 +30,15 @@ #include <string> #include <vector> #include <typeinfo> +#include <limits> +#include <algorithm> +#include <sstream> +#include <complex> +#include <deque> +#include <queue> + +#define min(A,B) please_protect_your_min_with_parentheses +#define max(A,B) please_protect_your_max_with_parentheses // the following file is automatically generated by cmake #include "split_test_helper.h" diff --git a/test/nullary.cpp b/test/nullary.cpp index 0bde253df..0df15c081 100644 --- a/test/nullary.cpp +++ b/test/nullary.cpp @@ -38,7 +38,7 @@ bool equalsIdentity(const MatrixType& A) } } for (Index i = 0; i < A.rows(); ++i) { - for (Index j = 0; j < std::min(i, A.cols()); ++j) { + for (Index j = 0; j < (std::min)(i, A.cols()); ++j) { offDiagOK = offDiagOK && (A(i,j) == zero); } } diff --git a/test/packetmath.cpp b/test/packetmath.cpp index a7a0cd132..279f080b0 100644 --- a/test/packetmath.cpp +++ b/test/packetmath.cpp @@ -128,7 +128,7 @@ template<typename Scalar> void packetmath() { data1[i] = internal::random<Scalar>()/RealScalar(PacketSize); data2[i] = internal::random<Scalar>()/RealScalar(PacketSize); - refvalue = std::max(refvalue,internal::abs(data1[i])); + refvalue = (std::max)(refvalue,internal::abs(data1[i])); } internal::pstore(data2, internal::pload<Packet>(data1)); @@ -264,16 +264,16 @@ template<typename Scalar> void packetmath_real() ref[0] = data1[0]; for (int i=0; i<PacketSize; ++i) - ref[0] = std::min(ref[0],data1[i]); + ref[0] = (std::min)(ref[0],data1[i]); VERIFY(internal::isApprox(ref[0], internal::predux_min(internal::pload<Packet>(data1))) && "internal::predux_min"); - CHECK_CWISE2(std::min, internal::pmin); - CHECK_CWISE2(std::max, internal::pmax); + CHECK_CWISE2((std::min), internal::pmin); + CHECK_CWISE2((std::max), internal::pmax); CHECK_CWISE1(internal::abs, internal::pabs); ref[0] = data1[0]; for (int i=0; i<PacketSize; ++i) - ref[0] = std::max(ref[0],data1[i]); + ref[0] = (std::max)(ref[0],data1[i]); VERIFY(internal::isApprox(ref[0], internal::predux_max(internal::pload<Packet>(data1))) && "internal::predux_max"); for (int i=0; i<PacketSize; ++i) diff --git a/test/prec_inverse_4x4.cpp b/test/prec_inverse_4x4.cpp index c40cf7399..8ae8311a7 100644 --- a/test/prec_inverse_4x4.cpp +++ b/test/prec_inverse_4x4.cpp @@ -58,7 +58,7 @@ template<typename MatrixType> void inverse_general_4x4(int repeat) MatrixType inv = m.inverse(); double error = double( (m*inv-MatrixType::Identity()).norm() * absdet / NumTraits<Scalar>::epsilon() ); error_sum += error; - error_max = std::max(error_max, error); + error_max = (std::max)(error_max, error); } std::cerr << "inverse_general_4x4, Scalar = " << type_name<Scalar>() << std::endl; double error_avg = error_sum / repeat; diff --git a/test/product.h b/test/product.h index 101766b18..40ae4d51b 100644 --- a/test/product.h +++ b/test/product.h @@ -29,7 +29,7 @@ template<typename Derived1, typename Derived2> bool areNotApprox(const MatrixBase<Derived1>& m1, const MatrixBase<Derived2>& m2, typename Derived1::RealScalar epsilon = NumTraits<typename Derived1::RealScalar>::dummy_precision()) { return !((m1-m2).cwiseAbs2().maxCoeff() < epsilon * epsilon - * std::max(m1.cwiseAbs2().maxCoeff(), m2.cwiseAbs2().maxCoeff())); + * (std::max)(m1.cwiseAbs2().maxCoeff(), m2.cwiseAbs2().maxCoeff())); } template<typename MatrixType> void product(const MatrixType& m) @@ -102,7 +102,7 @@ template<typename MatrixType> void product(const MatrixType& m) // test the previous tests were not screwed up because operator* returns 0 // (we use the more accurate default epsilon) - if (!NumTraits<Scalar>::IsInteger && std::min(rows,cols)>1) + if (!NumTraits<Scalar>::IsInteger && (std::min)(rows,cols)>1) { VERIFY(areNotApprox(m1.transpose()*m2,m2.transpose()*m1)); } @@ -111,7 +111,7 @@ template<typename MatrixType> void product(const MatrixType& m) res = square; res.noalias() += m1 * m2.transpose(); VERIFY_IS_APPROX(res, square + m1 * m2.transpose()); - if (!NumTraits<Scalar>::IsInteger && std::min(rows,cols)>1) + if (!NumTraits<Scalar>::IsInteger && (std::min)(rows,cols)>1) { VERIFY(areNotApprox(res,square + m2 * m1.transpose())); } @@ -123,7 +123,7 @@ template<typename MatrixType> void product(const MatrixType& m) res = square; res.noalias() -= m1 * m2.transpose(); VERIFY_IS_APPROX(res, square - (m1 * m2.transpose())); - if (!NumTraits<Scalar>::IsInteger && std::min(rows,cols)>1) + if (!NumTraits<Scalar>::IsInteger && (std::min)(rows,cols)>1) { VERIFY(areNotApprox(res,square - m2 * m1.transpose())); } @@ -147,7 +147,7 @@ template<typename MatrixType> void product(const MatrixType& m) res2 = square2; res2.noalias() += m1.transpose() * m2; VERIFY_IS_APPROX(res2, square2 + m1.transpose() * m2); - if (!NumTraits<Scalar>::IsInteger && std::min(rows,cols)>1) + if (!NumTraits<Scalar>::IsInteger && (std::min)(rows,cols)>1) { VERIFY(areNotApprox(res2,square2 + m2.transpose() * m1)); } diff --git a/test/qr_colpivoting.cpp b/test/qr_colpivoting.cpp index dd1f89bd6..cdcf060ef 100644 --- a/test/qr_colpivoting.cpp +++ b/test/qr_colpivoting.cpp @@ -31,7 +31,7 @@ template<typename MatrixType> void qr() typedef typename MatrixType::Index Index; Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols2 = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE); - Index rank = internal::random<Index>(1, std::min(rows, cols)-1); + Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; @@ -64,7 +64,7 @@ template<typename MatrixType, int Cols2> void qr_fixedsize() { enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; typedef typename MatrixType::Scalar Scalar; - int rank = internal::random<int>(1, std::min(int(Rows), int(Cols))-1); + int rank = internal::random<int>(1, (std::min)(int(Rows), int(Cols))-1); Matrix<Scalar,Rows,Cols> m1; createRandomPIMatrixOfRank(rank,Rows,Cols,m1); ColPivHouseholderQR<Matrix<Scalar,Rows,Cols> > qr(m1); diff --git a/test/qr_fullpivoting.cpp b/test/qr_fullpivoting.cpp index 175c293b3..d281b26a8 100644 --- a/test/qr_fullpivoting.cpp +++ b/test/qr_fullpivoting.cpp @@ -31,7 +31,7 @@ template<typename MatrixType> void qr() typedef typename MatrixType::Index Index; Index rows = internal::random<Index>(20,200), cols = internal::random<int>(20,200), cols2 = internal::random<int>(20,200); - Index rank = internal::random<Index>(1, std::min(rows, cols)-1); + Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); typedef typename MatrixType::Scalar Scalar; typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType; diff --git a/test/redux.cpp b/test/redux.cpp index 3e16797fd..daa219690 100644 --- a/test/redux.cpp +++ b/test/redux.cpp @@ -43,8 +43,8 @@ template<typename MatrixType> void matrixRedux(const MatrixType& m) { s += m1(i,j); p *= m1(i,j); - minc = std::min(internal::real(minc), internal::real(m1(i,j))); - maxc = std::max(internal::real(maxc), internal::real(m1(i,j))); + minc = (std::min)(internal::real(minc), internal::real(m1(i,j))); + maxc = (std::max)(internal::real(maxc), internal::real(m1(i,j))); } const Scalar mean = s/Scalar(RealScalar(rows*cols)); @@ -86,8 +86,8 @@ template<typename VectorType> void vectorRedux(const VectorType& w) { s += v[j]; p *= v[j]; - minc = std::min(minc, internal::real(v[j])); - maxc = std::max(maxc, internal::real(v[j])); + minc = (std::min)(minc, internal::real(v[j])); + maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.head(i).sum()), Scalar(1)); VERIFY_IS_APPROX(p, v.head(i).prod()); @@ -103,8 +103,8 @@ template<typename VectorType> void vectorRedux(const VectorType& w) { s += v[j]; p *= v[j]; - minc = std::min(minc, internal::real(v[j])); - maxc = std::max(maxc, internal::real(v[j])); + minc = (std::min)(minc, internal::real(v[j])); + maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.tail(size-i).sum()), Scalar(1)); VERIFY_IS_APPROX(p, v.tail(size-i).prod()); @@ -120,8 +120,8 @@ template<typename VectorType> void vectorRedux(const VectorType& w) { s += v[j]; p *= v[j]; - minc = std::min(minc, internal::real(v[j])); - maxc = std::max(maxc, internal::real(v[j])); + minc = (std::min)(minc, internal::real(v[j])); + maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.segment(i, size-2*i).sum()), Scalar(1)); VERIFY_IS_APPROX(p, v.segment(i, size-2*i).prod()); @@ -140,7 +140,7 @@ template<typename VectorType> void vectorRedux(const VectorType& w) void test_redux() { // the max size cannot be too large, otherwise reduxion operations obviously generate large errors. - int maxsize = std::min(100,EIGEN_TEST_MAX_SIZE); + int maxsize = (std::min)(100,EIGEN_TEST_MAX_SIZE); EIGEN_UNUSED_VARIABLE(maxsize); for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( matrixRedux(Matrix<float, 1, 1>()) ); diff --git a/test/sparse.h b/test/sparse.h index 9944a2934..81ce82e16 100644 --- a/test/sparse.h +++ b/test/sparse.h @@ -29,6 +29,15 @@ #include "main.h" #if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC && !defined(__clang__) + +#ifdef min +#undef min +#endif + +#ifdef max +#undef max +#endif + #include <tr1/unordered_map> #define EIGEN_UNORDERED_MAP_SUPPORT namespace std { diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp index d8ff06a33..a6c148591 100644 --- a/test/sparse_basic.cpp +++ b/test/sparse_basic.cpp @@ -34,7 +34,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; - double density = std::max(8./(rows*cols), 0.01); + double density = (std::max)(8./(rows*cols), 0.01); typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; typedef Matrix<Scalar,Dynamic,1> DenseVector; Scalar eps = 1e-6; @@ -207,7 +207,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re initSparse<Scalar>(density, refMat2, m2); int j0 = internal::random<int>(0,rows-2); int j1 = internal::random<int>(0,rows-2); - int n0 = internal::random<int>(1,rows-std::max(j0,j1)); + int n0 = internal::random<int>(1,rows-(std::max)(j0,j1)); VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0)); VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0)); diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp index 1d2183bc3..0082b56cd 100644 --- a/test/sparse_product.cpp +++ b/test/sparse_product.cpp @@ -58,7 +58,7 @@ template<typename SparseMatrixType> void sparse_product() typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; - double density = std::max(8./(rows*cols), 0.01); + double density = (std::max)(8./(rows*cols), 0.01); typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; typedef Matrix<Scalar,Dynamic,1> DenseVector; diff --git a/test/sparse_solvers.cpp b/test/sparse_solvers.cpp index aba61e6c0..12a1cb9b6 100644 --- a/test/sparse_solvers.cpp +++ b/test/sparse_solvers.cpp @@ -47,7 +47,7 @@ initSPD(double density, template<typename Scalar> void sparse_solvers(int rows, int cols) { - double density = std::max(8./(rows*cols), 0.01); + double density = (std::max)(8./(rows*cols), 0.01); typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; typedef Matrix<Scalar,Dynamic,1> DenseVector; // Scalar eps = 1e-6; diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp index b3249915e..5be4f5d9a 100644 --- a/test/sparse_vector.cpp +++ b/test/sparse_vector.cpp @@ -26,8 +26,8 @@ template<typename Scalar> 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 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> SparseVectorType; diff --git a/test/stable_norm.cpp b/test/stable_norm.cpp index 5bf249577..206a274d6 100644 --- a/test/stable_norm.cpp +++ b/test/stable_norm.cpp @@ -68,8 +68,8 @@ template<typename MatrixType> void stable_norm(const MatrixType& m) Index rows = m.rows(); Index cols = m.cols(); - Scalar big = internal::random<Scalar>() * (std::numeric_limits<RealScalar>::max() * RealScalar(1e-4)); - Scalar small = internal::random<Scalar>() * (std::numeric_limits<RealScalar>::min() * RealScalar(1e4)); + Scalar big = internal::random<Scalar>() * ((std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4)); + Scalar small = internal::random<Scalar>() * ((std::numeric_limits<RealScalar>::min)() * RealScalar(1e4)); MatrixType vzero = MatrixType::Zero(rows, cols), vrand = MatrixType::Random(rows, cols), diff --git a/test/triangular.cpp b/test/triangular.cpp index 73bb27cb5..3210761c1 100644 --- a/test/triangular.cpp +++ b/test/triangular.cpp @@ -242,7 +242,7 @@ void bug_159() void test_triangular() { - int maxsize = std::min(EIGEN_TEST_MAX_SIZE,20); + int maxsize = (std::min)(EIGEN_TEST_MAX_SIZE,20); for(int i = 0; i < g_repeat ; i++) { int r = internal::random<int>(2,maxsize); EIGEN_UNUSED_VARIABLE(r); |