/external/eigen/test/eigen2/ |
H A D | eigen2_inverse.cpp | 20 int cols = m.cols(); local 26 MatrixType m1 = MatrixType::Random(rows, cols), 27 m2(rows, cols), 28 mzero = MatrixType::Zero(rows, cols), 33 m1 = MatrixType::Random(rows, cols);
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H A D | eigen2_linearstructure.cpp | 22 int cols = m.cols(); local 26 MatrixType m1 = MatrixType::Random(rows, cols), 27 m2 = MatrixType::Random(rows, cols), 28 m3(rows, cols), 29 mzero = MatrixType::Zero(rows, cols); 35 c = ei_random<int>(0, cols-1); 66 VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1); 67 VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1); 68 VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m [all...] |
H A D | eigen2_map.cpp | 42 int rows = m.rows(), cols = m.cols(), size = rows*cols; local 52 Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols); 53 Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2 54 Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols); 55 MatrixType ma1 = Map<MatrixType>(array1, rows, cols); [all...] |
H A D | eigen2_miscmatrices.cpp | 22 int cols = m.cols(); local 24 int r = ei_random<int>(0, rows-1), r2 = ei_random<int>(0, rows-1), c = ei_random<int>(0, cols-1); 25 VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1)); 26 MatrixType m1 = MatrixType::Ones(rows,cols);
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H A D | eigen2_newstdvector.cpp | 19 int cols = m.cols(); local 20 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 21 std::vector<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
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H A D | eigen2_qtvector.cpp | 24 int cols = m.cols(); local 25 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 26 QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
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H A D | eigen2_stdvector.cpp | 18 int cols = m.cols(); local 19 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 20 std::vector<MatrixType, aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
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H A D | eigen2_sum.cpp | 17 int cols = m.cols(); local 19 MatrixType m1 = MatrixType::Random(rows, cols); 21 VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1)); 22 VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy 24 for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
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H A D | eigen2_svd.cpp | 19 int cols = m.cols(); local 23 MatrixType a = MatrixType::Random(rows,cols); 26 Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x(cols,1), x2(cols,1); 34 MatrixType sigma = MatrixType::Zero(rows,cols); 36 sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal(); 37 matU.block(0,0,rows,cols) = svd.matrixU(); 42 if (rows==cols) [all...] |
H A D | eigen2_swap.cpp | 32 int cols = m.cols(); local 35 MatrixType m1 = MatrixType::Random(rows,cols); 36 MatrixType m2 = MatrixType::Random(rows,cols) + Scalar(100) * MatrixType::Identity(rows,cols); 37 OtherMatrixType m3 = OtherMatrixType::Random(rows,cols) + Scalar(200) * OtherMatrixType::Identity(rows,cols); 58 m1.swap(m2.block(0,0,rows,cols));
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/external/eigen/test/ |
H A D | eigen2support.cpp | 20 Index cols = m.cols(); local 22 MatrixType m1 = MatrixType::Random(rows, cols), 23 m3(rows, cols); 30 VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1); 31 VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
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H A D | eigensolver_generalized_real.cpp | 21 Index cols = m.cols(); local 26 MatrixType a = MatrixType::Random(rows,cols); 27 MatrixType b = MatrixType::Random(rows,cols); 28 MatrixType a1 = MatrixType::Random(rows,cols); 29 MatrixType b1 = MatrixType::Random(rows,cols);
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H A D | inverse.cpp | 22 Index cols = m.cols(); local 26 MatrixType m1(rows, cols), 27 m2(rows, cols), 65 MatrixType m3 = v3*v3.transpose(), m4(rows,cols);
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H A D | jacobi.cpp | 19 Index cols = m.cols(); local 28 const MatrixType a(MatrixType::Random(rows, cols)); 48 Index p = internal::random<Index>(0, cols-1); 51 q = internal::random<Index>(0, cols-1);
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H A D | linearstructure.cpp | 22 Index cols = m.cols(); local 26 MatrixType m1 = MatrixType::Random(rows, cols), 27 m2 = MatrixType::Random(rows, cols), 28 m3(rows, cols); 34 c = internal::random<Index>(0, cols-1); 65 VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1); 66 VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1)); 67 VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1); 68 VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s [all...] |
H A D | mapstaticmethods.cpp | 72 int rows = m.rows(), cols = m.cols(); local 76 PlainObjectType::Map(ptr, rows, cols).setZero(); 77 PlainObjectType::MapAligned(ptr, rows, cols).setZero(); 78 PlainObjectType::Map(const_ptr, rows, cols).sum(); 79 PlainObjectType::MapAligned(const_ptr, rows, cols).sum(); 81 PlainObjectType::Map(ptr, rows, cols, InnerStride<>(i)).setZero(); 82 PlainObjectType::MapAligned(ptr, rows, cols, InnerStride<>(i)).setZero(); 83 PlainObjectType::Map(const_ptr, rows, cols, InnerStride<>(i)).sum(); 84 PlainObjectType::MapAligned(const_ptr, rows, cols, InnerStrid [all...] |
H A D | miscmatrices.cpp | 21 Index cols = m.cols(); local 23 Index r = internal::random<Index>(0, rows-1), r2 = internal::random<Index>(0, rows-1), c = internal::random<Index>(0, cols-1); 24 VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1)); 25 MatrixType m1 = MatrixType::Ones(rows,cols);
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H A D | product_trmv.cpp | 22 Index cols = m.cols(); local 24 MatrixType m1 = MatrixType::Random(rows, cols), 25 m3(rows, cols); 30 m1 = MatrixType::Random(rows, cols);
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H A D | qtvector.cpp | 24 Index cols = m.cols(); local 25 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 26 QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
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H A D | sizeoverflow.cpp | 24 void triggerMatrixBadAlloc(Index rows, Index cols) argument 26 VERIFY_THROWS_BADALLOC( MatrixType m(rows, cols) ); 27 VERIFY_THROWS_BADALLOC( MatrixType m; m.resize(rows, cols) ); 28 VERIFY_THROWS_BADALLOC( MatrixType m; m.conservativeResize(rows, cols) ); 41 // there are 2 levels of overflow checking. first in PlainObjectBase.h we check for overflow in rows*cols computations.
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H A D | special_numbers.cpp | 16 int cols = internal::random<int>(1,300); local 22 MatType m1 = MatType::Random(rows,cols), 23 mnan = MatType::Random(rows,cols), 24 minf = MatType::Random(rows,cols), 25 mboth = MatType::Random(rows,cols); 30 mnan(internal::random<int>(0,rows-1), internal::random<int>(0,cols-1)) = nan; 31 minf(internal::random<int>(0,rows-1), internal::random<int>(0,cols-1)) = inf;
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H A D | stddeque.cpp | 21 Index cols = m.cols(); local 22 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 23 std::deque<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
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H A D | stdlist.cpp | 21 Index cols = m.cols(); local 22 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 23 std::list<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
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H A D | stdvector.cpp | 18 typename MatrixType::Index cols = m.cols(); local 19 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 20 std::vector<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
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H A D | stdvector_overload.cpp | 32 typename MatrixType::Index cols = m.cols(); local 33 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols); 34 std::vector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
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