| /external/eigen/test/ |
| linearstructure.cpp | 26 Index rows = m.rows(); local
31 MatrixType m1 = MatrixType::Random(rows, cols),
32 m2 = MatrixType::Random(rows, cols),
33 m3(rows, cols);
38 Index r = internal::random<Index>(0, rows-1),
70 VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
71 VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1));
72 VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
73 VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1)
[all...] |
| sparse_solvers.cpp | 17 Matrix<Scalar,Dynamic,Dynamic> aux(refMat.rows(),refMat.cols());
27 for (int i=j ; i<sparseMat.rows(); ++i)
33 template<typename Scalar> void sparse_solvers(int rows, int cols)
35 double density = (std::max)(8./(rows*cols), 0.01);
40 DenseVector vec1 = DenseVector::Random(rows);
48 SparseMatrix<Scalar> m2(rows, cols);
49 DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
64 //Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerIndexPtr, Scalar* valuePtr
65 MappedSparseMatrix<Scalar> mm2(rows, cols, cm2.nonZeros(), cm2.outerIndexPtr(), cm2.innerIndexPtr(), cm2.valuePtr());
80 SparseMatrix<Scalar> matB(rows, rows)
[all...] |
| vectorwiseop.cpp | 23 Index rows = m.rows(); local
25 Index r = internal::random<Index>(0, rows-1),
28 ArrayType m1 = ArrayType::Random(rows, cols),
29 m2(rows, cols),
30 m3(rows, cols);
32 ColVectorType colvec = ColVectorType::Random(rows);
118 Array<bool,Dynamic,Dynamic> mb(rows,cols);
140 Index rows = m.rows(); local
[all...] |
| basicstuff.cpp | 21 Index rows = m.rows(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols),
28 m3(rows, cols),
29 mzero = MatrixType::Zero(rows, cols),
30 square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
31 VectorType v1 = VectorType::Random(rows),
32 vzero = VectorType::Zero(rows);
152 Index rows = m.rows(); local
[all...] |
| sparse_block.cpp | 28 const Index rows = ref.rows(); local
36 double density = (std::max)(8./(rows*cols), 0.01);
44 SparseMatrixType m(rows, cols);
45 DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
54 Index i = internal::random<Index>(0,rows-2);
56 Index h = internal::random<Index>(1,rows-i);
114 for(Index r=0; r<rows; r++)
123 DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
124 SparseMatrixType m2(rows, cols)
[all...] |
| jacobi.cpp | 18 Index rows = m.rows(); local
28 const MatrixType a(MatrixType::Random(rows, cols));
35 Index p = internal::random<Index>(0, rows-1);
38 q = internal::random<Index>(0, rows-1);
|
| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| ConstrainedConjGrad.h | 55 Index rows = C.rows(), cols = C.cols(); local
57 TmpVec d(rows), e(rows), l(cols), p(rows), q(rows), r(rows);
64 for (Index i = 0; i < rows; ++i)
119 std::vector<bool> satured(C.rows());
124 SparseMatrix<Scalar,RowMajor> CINV(C.rows(), C.cols())
[all...] |
| /external/gemmlowp/meta/ |
| test_streams_correctness.cc | 36 void prepare_row_major_data(int rows, int elements, int stride, std::uint8_t* data) {
37 for (int i = 0; i < rows * stride; ++i) {
40 for (int i = 0; i < rows; ++i) {
59 void print_out(std::uint8_t* result, int rows, int elements) {
60 int size = rows * ((elements + 7) / 8) * 8;
67 bool check(std::uint8_t* result, int rows, int elements) {
71 int chunk_index = i * rows * 8;
73 for (int j = 0; j < rows; ++j) {
82 int leftover_index = chunks * rows * 8;
84 for (int i = 0; i < rows; ++i)
[all...] |
| /external/libvpx/libvpx/test/ |
| active_map_test.cc | 56 map.rows = (kHeight + 15) / 16;
58 ASSERT_EQ(map.rows, 9u);
64 map.rows = (kHeight + 15) / 16;
|
| /external/mesa3d/src/compiler/glsl/tests/ |
| copy_constant_to_storage_tests.cpp | 41 void int_test(unsigned rows);
42 void uint_test(unsigned rows);
43 void bool_test(unsigned rows);
45 void float_test(unsigned columns, unsigned rows);
68 copy_constant_to_storage::int_test(unsigned rows)
71 generate_data(mem_ctx, GLSL_TYPE_INT, 1, rows, val);
88 copy_constant_to_storage::uint_test(unsigned rows)
91 generate_data(mem_ctx, GLSL_TYPE_UINT, 1, rows, val);
108 copy_constant_to_storage::float_test(unsigned columns, unsigned rows)
111 generate_data(mem_ctx, GLSL_TYPE_FLOAT, columns, rows, val)
[all...] |
| /external/skia/src/sksl/ir/ |
| SkSLIndexExpression.h | 23 switch (type.rows()) {
30 switch (type.rows()) {
38 switch (type.rows()) {
|
| /external/skqp/src/sksl/ir/ |
| SkSLIndexExpression.h | 23 switch (type.rows()) {
30 switch (type.rows()) {
38 switch (type.rows()) {
|
| /external/tensorflow/tensorflow/core/kernels/ |
| self_adjoint_eig_v2_op_impl.h | 57 const int64 rows = inputs[0].rows(); variable
58 if (rows == 0) {
59 // If X is an empty matrix (0 rows, 0 col), X * X' == X.
|
| /external/webrtc/webrtc/system_wrappers/include/ |
| aligned_array.h | 23 AlignedArray(size_t rows, size_t cols, size_t alignment)
24 : rows_(rows),
70 size_t rows() const { function in class:webrtc::AlignedArray
|
| /frameworks/base/core/tests/coretests/src/android/database/sqlite/ |
| SQLiteCursorTest.java | 87 Set<Integer> rows = new HashSet<Integer>(); local
92 rows.add(j); // store in a hashtable so we can verify the results from cursor later on
96 assertEquals(N, rows.size());
108 assertTrue(rows.contains(val));
109 assertTrue(rows.remove(val));
111 // did I see all the rows in the table?
112 assertTrue(rows.isEmpty());
115 rows = new HashSet<Integer>();
119 rows.add(j);
128 assertEquals(M, rows.size())
[all...] |
| /external/eigen/Eigen/src/Householder/ |
| HouseholderSequence.h | 93 return Block<const VectorsType,Dynamic,1>(h.m_vectors, start, k, h.rows()-start, 1);
105 return Block<const VectorsType,1,Dynamic>(h.m_vectors, k, start, 1, h.rows()-start).transpose();
150 * i-th column). If \p v has fewer columns than rows, then the Householder sequence contains as many
176 /** \brief Number of rows of transformation viewed as a matrix.
177 * \returns Number of rows
180 Index rows() const { return Side==OnTheLeft ? m_vectors.rows() : m_vectors.cols(); } function in class:Eigen::HouseholderSequence
186 Index cols() const { return rows(); }
236 AutoAlign|ColMajor, DestType::MaxRowsAtCompileTime, 1> workspace(rows());
244 workspace.resize(rows());
[all...] |
| /external/ImageMagick/coders/ |
| dib.c | 186 (void) ResetMagickMemory(pixels,0,(size_t) image->columns*image->rows*
191 q=pixels+(size_t) image->columns*image->rows;
192 for (y=0; y < (ssize_t) image->rows; )
282 if (SetImageProgress(image,LoadImageTag,y,image->rows) == MagickFalse)
351 for (y=0; y < (ssize_t) image->rows; y++)
370 if (SetImageProgress(image,LoadImageTag,y,image->rows) == MagickFalse)
571 image->rows=(size_t) MagickAbsoluteValue(dib_info.height);
601 if ((geometry.height != 0) && (geometry.height < image->rows))
602 image->rows=geometry.height;
604 status=SetImageExtent(image,image->columns,image->rows,exception)
[all...] |
| /external/eigen/Eigen/src/QR/ |
| CompleteOrthogonalDecomposition.h | 93 CompleteOrthogonalDecomposition(Index rows, Index cols)
94 : m_cpqr(rows, cols), m_zCoeffs((std::min)(rows, cols)), m_temp(cols) {}
104 * CompleteOrthogonalDecomposition<MatrixType> cod(matrix.rows(),
114 : m_cpqr(matrix.rows(), matrix.cols()),
115 m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
130 m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
281 inline Index rows() const { return m_cpqr.rows(); } function in class:Eigen::CompleteOrthogonalDecomposition
419 const Index rows = m_cpqr.rows() local
[all...] |
| /external/eigen/unsupported/Eigen/src/Skyline/ |
| SkylineInplaceLU.h | 37 : /*m_matrix(matrix.rows(), matrix.cols()),*/ m_flags(flags), m_status(0), m_lu(matrix) {
121 const size_t rows = m_lu.rows(); local
124 eigen_assert(rows == cols && "We do not (yet) support rectangular LU.");
127 for (Index row = 0; row < rows; row++) {
138 for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
157 for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
170 for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
185 const size_t rows = m_lu.rows(); local
308 const size_t rows = m_lu.rows(); local
[all...] |
| /external/eigen/Eigen/src/Core/ |
| CwiseNullaryOp.h | 68 CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
69 : m_rows(rows), m_cols(cols), m_functor(func)
71 eigen_assert(rows >= 0
72 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
78 EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); } function in class:Eigen::CwiseNullaryOp
95 * The parameters \a rows and \a cols are the number of rows and of columns of
99 * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
109 DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
111 return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func)
[all...] |
| EigenBase.h | 57 /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
59 inline Index rows() const { return derived().rows(); } function in struct:Eigen::EigenBase
60 /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
63 /** \returns the number of coefficients, which is rows()*cols().
64 * \sa rows(), cols(), SizeAtCompileTime. */
66 inline Index size() const { return rows() * cols(); }
81 typename Dest::PlainObject res(rows(),cols());
93 typename Dest::PlainObject res(rows(),cols());
|
| /external/ImageMagick/Magick++/tests/ |
| readWriteImages.cpp | 71 if (firstIter->rows() != secondIter->rows())
75 << " Image rows " << secondIter->rows()
77 << firstIter->rows()
87 << firstIter->rows()
|
| /external/eigen/bench/ |
| BenchUtil.h | 24 mat.setRandom();// = MatrixType::random(mat.rows(), mat.cols());
51 dst.resize(src.rows(),src.cols());
53 for (int i=0; i<src.rows(); ++i)
67 for (int i=0; i<src.rows(); ++i)
78 dst.resize(src.rows(),src.cols());
80 for (int i=0; i<src.rows(); ++i)
|
| /external/eigen/unsupported/Eigen/src/AutoDiff/ |
| AutoDiffJacobian.h | 83 ActiveValue av(jac.rows());
86 for (Index j=0; j<jac.rows(); j++)
87 av[j].derivatives().resize(x.rows());
90 ax[i].derivatives() = DerivativeType::Unit(x.rows(),i);
98 for (Index i=0; i<jac.rows(); i++)
|
| /external/libvpx/libvpx/vp9/common/ |
| vp9_debugmodes.c | 29 int rows = cm->mi_rows; local
34 for (mi_row = 0; mi_row < rows; mi_row++) {
51 int rows = cm->mi_rows; local
62 for (mi_row = 0; mi_row < rows; mi_row++) {
76 for (mi_row = 0; mi_row < rows; mi_row++) {
|
