/external/eigen/test/eigen2/ |
H A D | eigen2_eigensolver.cpp | 22 int rows = m.rows(); local 33 MatrixType a = MatrixType::Random(rows,cols); 34 MatrixType a1 = MatrixType::Random(rows,cols); 37 MatrixType b = MatrixType::Random(rows,cols); 38 MatrixType b1 = MatrixType::Random(rows,cols); 56 gEval = GslTraits<RealScalar>::createVector(rows); 105 int rows = m.rows(); local 116 MatrixType a = MatrixType::Random(rows,col [all...] |
H A D | eigen2_nomalloc.cpp | 30 int rows = m.rows(); local 33 MatrixType m1 = MatrixType::Random(rows, cols), 34 m2 = MatrixType::Random(rows, cols), 35 m3(rows, cols), 36 mzero = MatrixType::Zero(rows, cols), 38 ::Identity(rows, rows), 40 ::Random(rows, rows); [all...] |
H A D | eigen2_sparse_product.cpp | 14 const int rows = ref.rows(); local 19 double density = std::max(8./(rows*cols), 0.01); 25 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); 26 DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows); 27 DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows); 28 DenseMatrix dm4 = DenseMatrix::Zero(rows, row [all...] |
H A D | eigen2_triangular.cpp | 20 int rows = m.rows(); local 23 MatrixType m1 = MatrixType::Random(rows, cols), 24 m2 = MatrixType::Random(rows, cols), 25 m3(rows, cols), 26 m4(rows, cols), 27 r1(rows, cols), 28 r2(rows, cols), 29 mzero = MatrixType::Zero(rows, cols), 30 mones = MatrixType::Ones(rows, col [all...] |
H A D | eigen2_visitor.cpp | 16 int rows = p.rows(); local 21 m = MatrixType::Random(rows, cols); 30 for(int i = 0; i < rows; i++)
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H A D | gsl_helper.h | 28 static Matrix createMatrix(int rows, int cols) { return gsl_matrix_alloc(rows,cols); } argument 63 static Matrix createMatrix(int rows, int cols) { return gsl_matrix_complex_alloc(rows,cols); } argument 100 res = gsl_matrix_alloc(m.rows(), m.cols()); 101 for (int i=0 ; i<m.rows() ; ++i) 110 for (int i=0 ; i<res.rows() ; ++i) 128 for (int i=0 ; i<res.rows() ; ++i) 135 res = gsl_matrix_complex_alloc(m.rows(), m.cols()); 136 for (int i=0 ; i<m.rows() ; [all...] |
/external/eigen/test/ |
H A D | eigensolver_complex.cpp | 17 by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */ 25 VERIFY(vec1.rows() == vec2.rows()); 26 for (int k = 1; k <= vec1.rows(); ++k) 39 Index rows = m.rows(); local 48 MatrixType a = MatrixType::Random(rows,cols); 67 MatrixType z = MatrixType::Zero(rows,cols); 71 MatrixType id = MatrixType::Identity(rows, cols); 74 if (rows > [all...] |
H A D | eigensolver_selfadjoint.cpp | 21 Index rows = m.rows(); local 32 MatrixType a = MatrixType::Random(rows,cols); 33 MatrixType a1 = MatrixType::Random(rows,cols); 37 MatrixType b = MatrixType::Random(rows,cols); 38 MatrixType b1 = MatrixType::Random(rows,cols); 85 MatrixType id = MatrixType::Identity(rows, cols); 105 if (rows > 1)
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H A D | integer_types.cpp | 27 Index rows = m.rows(); local 30 MatrixType m1(rows, cols), 31 m2 = MatrixType::Random(rows, cols), 32 mzero = MatrixType::Zero(rows, cols); 35 m1 = MatrixType::Random(rows, cols); 61 Index rows = m.rows(); local 66 MatrixType m1(rows, cols), 67 m2 = MatrixType::Random(rows, col [all...] |
H A D | lu.cpp | 22 Index rows, cols, cols2; local 25 rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE); 29 rows = MatrixType::RowsAtCompileTime; 52 Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); 55 VERIFY((MatrixType::Zero(rows,cols).fullPivLu().image(MatrixType::Zero(rows,cols)).cols() == 1)); 57 MatrixType m1(rows, cols), m3(rows, cols2); 59 createRandomPIMatrixOfRank(rank, rows, cols, m1); 69 MatrixType u(rows,col 137 Index rows = internal::random<Index>(1,4); local [all...] |
H A D | map.cpp | 52 Index rows = m.rows(), cols = m.cols(), size = rows*cols; local 62 Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols); 63 Map<MatrixType>(array2, rows, cols) = Map<MatrixType>(array1, rows, cols); 64 Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols); 65 MatrixType ma1 = Map<MatrixType>(array1, rows, col [all...] |
H A D | permutationmatrices.cpp | 27 Index rows = m.rows(); local 30 MatrixType m_original = MatrixType::Random(rows,cols); 32 randomPermutationVector(lv, rows); 39 for (int i=0; i<rows; i++) 57 randomPermutationVector(lv2, rows); 65 identityp.setIdentity(rows); 85 if(rows>1 && cols>1) 88 Index i = internal::random<Index>(0, rows-1); 90 do j = internal::random<Index>(0, rows [all...] |
H A D | product_selfadjoint.cpp | 22 Index rows = m.rows(); local 25 MatrixType m1 = MatrixType::Random(rows, cols), 26 m2 = MatrixType::Random(rows, cols), 28 VectorType v1 = VectorType::Random(rows), 29 v2 = VectorType::Random(rows), 30 v3(rows); 31 RowVectorType r1 = RowVectorType::Random(rows), 32 r2 = RowVectorType::Random(rows); 33 RhsMatrixType m4 = RhsMatrixType::Random(rows,1 [all...] |
H A D | product_symm.cpp | 23 Index rows = size; local 26 MatrixType m1 = MatrixType::Random(rows, cols), 27 m2 = MatrixType::Random(rows, cols), m3; 32 Rhs2 rhs2 = Rhs2::Random(othersize, rows), rhs22(othersize, rows), rhs23(othersize, rows);
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H A D | product_trmm.cpp | 13 void trmm(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), argument 26 TriMatrix mat(rows,cols), tri(rows,cols), triTr(cols,rows); 29 OnTheLeft ge_left(otherCols,rows); 65 void trmv(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) argument 67 trmm<Scalar,Mode,TriOrder,ColMajor,ColMajor,1>(rows,cols,1); 71 void trmm(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int otherCols = internal::random<int>(1,EIGEN_TEST_MAX_SIZE)) argument 73 trmm<Scalar,Mode,TriOrder,OtherOrder,ResOrder,Dynamic>(rows,cols,otherCols);
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H A D | qr.cpp | 17 Index rows = m.rows(); local 24 MatrixType a = MatrixType::Random(rows,cols);
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H A D | qr_colpivoting.cpp | 18 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); local 19 Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); 26 createRandomPIMatrixOfRank(rank,rows,cols,m1);
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H A D | qr_fullpivoting.cpp | 18 Index rows = internal::random<Index>(20,200), cols = internal::random<int>(20,200), cols2 = internal::random<int>(20,200); local 19 Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); 25 createRandomPIMatrixOfRank(rank,rows,cols,m1); 39 for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
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H A D | redux.cpp | 18 Index rows = m.rows(); local 21 MatrixType m1 = MatrixType::Random(rows, cols); 25 MatrixType m1_for_prod = MatrixType::Ones(rows, cols) + Scalar(0.2) * m1; 27 VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1)); 28 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 31 for(int i = 0; i < rows; i++) 38 const Scalar mean = s/Scalar(RealScalar(rows*cols)); 47 Index r0 = internal::random<Index>(0,rows [all...] |
H A D | sparse_permutations.cpp | 16 const Index rows = ref.rows(); local 24 double density = (std::max)(8./(rows*cols), 0.01); 26 SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols); 28 DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d;
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H A D | stable_norm.cpp | 53 Index rows = m.rows(); local 59 MatrixType vzero = MatrixType::Zero(rows, cols), 60 vrand = MatrixType::Random(rows, cols), 61 vbig(rows, cols), 62 vsmall(rows,cols);
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H A D | triangular.cpp | 22 typename MatrixType::Index rows = m.rows(); local 25 MatrixType m1 = MatrixType::Random(rows, cols), 26 m2 = MatrixType::Random(rows, cols), 27 m3(rows, cols), 28 m4(rows, cols), 29 r1(rows, cols), 30 r2(rows, cols); 31 VectorType v2 = VectorType::Random(rows); 36 if (rows*col 130 Index rows = m.rows(); local [all...] |
H A D | visitor.cpp | 17 Index rows = p.rows(); local 22 m = MatrixType::Random(rows, cols); 31 for(Index i = 0; i < rows; i++)
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/external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
H A D | ConstrainedConjGrad.h | 59 Index rows = C.rows(), cols = C.cols(); local 61 TmpVec d(rows), e(rows), l(cols), p(rows), q(rows), r(rows); 66 for (Index i = 0; i < rows; ++i) 119 std::vector<bool> satured(C.rows()); 124 SparseMatrix<Scalar,RowMajor> CINV(C.rows(), [all...] |
H A D | IncompleteLU.h | 34 Index rows() const { return m_lu.rows(); } function in class:Eigen::IncompleteLU 84 eigen_assert(cols()==b.rows() 85 && "IncompleteLU::solve(): invalid number of rows of the right hand side matrix b");
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