| /external/eigen/test/ |
| array.cpp | 19 Index rows = m.rows(); local
22 ArrayType m1 = ArrayType::Random(rows, cols),
23 m2 = ArrayType::Random(rows, cols),
24 m3(rows, cols);
26 ColVectorType cv1 = ColVectorType::Random(rows);
34 VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1);
36 VERIFY_IS_APPROX(m1 - s1, m1 - ArrayType::Constant(rows,cols,s1));
37 VERIFY_IS_APPROX(s1 - m1, ArrayType::Constant(rows,cols,s1) - m1);
38 VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - ArrayType::Constant(rows,cols,s2) )
93 Index rows = m.rows(); local
162 Index rows = m.rows(); local
224 Index rows = m.rows(); local
243 Index rows = m.rows(); local
[all...] |
| sparse_vector.cpp | 12 template<typename Scalar,typename Index> void sparse_vector(int rows, int cols)
14 double densityMat = (std::max)(8./(rows*cols), 0.01);
15 double densityVec = (std::max)(8./float(rows), 0.1);
22 SparseMatrixType m1(rows,rows);
23 SparseVectorType v1(rows), v2(rows), v3(rows);
24 DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
[all...] |
| product.h | 34 Index rows = m.rows(); local
39 MatrixType m1 = MatrixType::Random(rows, cols),
40 m2 = MatrixType::Random(rows, cols),
41 m3(rows, cols);
43 identity = RowSquareMatrixType::Identity(rows, rows),
44 square = RowSquareMatrixType::Random(rows, rows),
45 res = RowSquareMatrixType::Random(rows, rows)
[all...] |
| special_numbers.cpp | 15 int rows = 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;
|
| array_reverse.cpp | 22 Index rows = m.rows(); local
27 MatrixType m1 = MatrixType::Random(rows, cols);
28 VectorType v1 = VectorType::Random(rows);
32 for ( int i = 0; i < rows; i++ ) {
34 VERIFY_IS_APPROX(m1_r(i, j), m1(rows - 1 - i, cols - 1 - j));
40 for ( int i = 0; i < rows; i++ ) {
42 VERIFY_IS_APPROX(m1_rd(i, j), m1(rows - 1 - i, cols - 1 - j));
48 for ( int i = 0; i < rows; i++ ) {
50 VERIFY_IS_APPROX(m1_rb(i, j), m1(rows - 1 - i, cols - 1 - j))
[all...] |
| 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, cols)
[all...] |
| 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
45 MatrixType a = MatrixType::Random(rows,cols);
60 ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
64 if (rows > 2) {
75 MatrixType z = MatrixType::Zero(rows,cols)
[all...] |
| inverse.cpp | 21 Index rows = m.rows(); local
26 MatrixType m1(rows, cols),
27 m2(rows, cols),
28 identity = MatrixType::Identity(rows, rows);
29 createRandomPIMatrixOfRank(rows,rows,rows,m1);
64 VectorType v3 = VectorType::Random(rows);
[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...] |
| /external/eigen/bench/ |
| spmv.cpp | 28 // mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
31 // // mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
32 // // lhs._valuePtr(), lhs.rows(), DST, dst_stride);
40 int rows = size; local
51 rows = atoi(argv[i]+1);
76 std::cout << argv[0] << " r<nb rows> c<nb columns> n<non zeros per column> t<nb tries> p<nb repeats>\n";
80 std::cout << "SpMV " << rows << " x " << cols << " with " << nnzPerCol << " non zeros per column. (" << repeats << " repeats, and " << tries << " tries)\n\n";
82 EigenSparseMatrix sm(rows,cols);
83 DenseVector dv(cols), res(rows);
91 fillMatrix2(nnzPerCol, rows, cols, sm)
[all...] |
| /external/eigen/test/eigen2/ |
| eigen2_array.cpp | 23 int rows = m.rows(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols),
28 m3(rows, cols);
35 VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1);
36 VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
58 int rows = m.rows(); local
61 int r = ei_random<int>(0, rows-1)
[all...] |
| eigen2_adjoint.cpp | 22 int rows = m.rows(); local
29 MatrixType m1 = MatrixType::Random(rows, cols),
30 m2 = MatrixType::Random(rows, cols),
31 m3(rows, cols),
32 square = SquareMatrixType::Random(rows, rows);
33 VectorType v1 = VectorType::Random(rows),
34 v2 = VectorType::Random(rows),
35 v3 = VectorType::Random(rows),
[all...] |
| product.h | 36 int rows = m.rows(); local
41 MatrixType m1 = MatrixType::Random(rows, cols),
42 m2 = MatrixType::Random(rows, cols),
43 m3(rows, cols);
45 identity = RowSquareMatrixType::Identity(rows, rows),
46 square = RowSquareMatrixType::Random(rows, rows),
47 res = RowSquareMatrixType::Random(rows, rows)
[all...] |
| /prebuilts/gdb/darwin-x86/lib/python2.7/plat-mac/lib-scriptpackages/StdSuites/ |
| Table_Suite.py | 42 class rows(aetools.ComponentItem): class in inherits:aetools.ComponentItem
43 """rows - """
46 row = rows
66 rows._superclassnames = []
67 rows._privpropdict = {
69 rows._privelemdict = {
89 'crow' : rows,
|
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/plat-mac/lib-scriptpackages/StdSuites/ |
| Table_Suite.py | 42 class rows(aetools.ComponentItem): class in inherits:aetools.ComponentItem
43 """rows - """
46 row = rows
66 rows._superclassnames = []
67 rows._privpropdict = {
69 rows._privelemdict = {
89 'crow' : rows,
|
| /external/eigen/doc/ |
| AsciiQuickReference.txt | 6 Matrix<double, 3, 3> A; // Fixed rows and cols. Same as Matrix3d.
7 Matrix<double, 3, Dynamic> B; // Fixed rows, dynamic cols.
19 C.rows() // size(C,1) // number of rows
31 7, 8, 9; // and then the rows are stacked.
36 MatrixXd::Identity(rows,cols) // eye(rows,cols)
37 C.setIdentity(rows,cols) // C = eye(rows,cols)
38 MatrixXd::Zero(rows,cols) // zeros(rows,cols
[all...] |
| /external/ceres-solver/internal/ceres/ |
| incomplete_lq_factorization_test.cc | 48 EXPECT_EQ(expected.rows()[i], actual.rows()[i]);
84 int* rows = matrix.mutable_rows(); local
90 rows[i] = idx;
100 rows[10] = idx;
148 for (int idx = matrix.rows()[1]; idx < matrix.rows()[2]; ++idx) {
149 EXPECT_EQ(matrix.cols()[idx], idx - matrix.rows()[1]);
150 EXPECT_EQ(matrix.values()[idx], dense_vector(idx - matrix.rows()[1]));
159 EXPECT_EQ(matrix.cols()[matrix.rows()[2]], 0)
[all...] |
| /external/dng_sdk/source/ |
| dng_reference.h | 44 uint32 rows,
53 uint32 rows,
62 uint32 rows,
73 uint32 rows,
85 uint32 rows,
97 uint32 rows,
109 uint32 rows,
121 uint32 rows,
133 uint32 rows,
145 uint32 rows,
[all...] |
| dng_bottlenecks.h | 55 uint32 rows,
65 uint32 rows,
75 uint32 rows,
87 uint32 rows,
100 uint32 rows,
113 uint32 rows,
126 uint32 rows,
139 uint32 rows,
152 uint32 rows,
165 uint32 rows,
[all...] |
| /external/chromium-trace/catapult/tracing/tracing/ui/tracks/ |
| async_slice_group_track.html | 63 * Breaks up the list of slices into N rows, each of which is a list of
69 * subSlices recursively into rows below parent slice according to which
80 var findLevel = function(sliceToPut, rows, n) {
81 if (n >= rows.length)
82 return true; // We always can make empty rows to put the slice.
83 var subRow = rows[n];
92 if (!findLevel(sliceToPut.subSlices[i], rows, n + 1))
117 // Fit subSlices recursively into rows below parent.
118 var fitSubSlicesRecursively = function(subSlices, level, rows) {
121 if (level === rows.length
[all...] |
| /external/opencv3/modules/core/src/ |
| cuda_gpu_mat.cpp | 50 flags(Mat::MAGIC_VAL + (type_ & Mat::TYPE_MASK)), rows(rows_), cols(cols_),
64 if (rows == 1)
72 dataend += step * (rows - 1) + minstep;
76 flags(Mat::MAGIC_VAL + (type_ & Mat::TYPE_MASK)), rows(size_.height), cols(size_.width),
90 if (rows == 1)
98 dataend += step * (rows - 1) + minstep;
110 rows = m.rows;
114 CV_Assert( 0 <= rowRange_.start && rowRange_.start <= rowRange_.end && rowRange_.end <= m.rows );
116 rows = rowRange_.size()
[all...] |
| /external/javasqlite/src/main/java/SQLite/ |
| TableResult.java | 39 * Number of rows in the result set.
57 * Rows of the result set. Each row is stored as a String array.
60 public Vector rows; field in class:TableResult
63 * Maximum number of rows to hold in the table.
69 * Flag to indicate Maximum number of rows condition.
83 * Create an empty result set with maximum number of rows.
98 rows = new Vector();
130 rows.addElement(rowdata);
150 String row[] = (String[]) rows.elementAt(i);
|
| /external/opencv3/modules/cudev/include/opencv2/cudev/grid/detail/ |
| split_merge.hpp | 63 __global__ void mergeC2(const Src1Ptr src1, const Src2Ptr src2, GlobPtr<DstType> dst, const MaskPtr mask, const int rows, const int cols)
70 if (x >= cols || y >= rows || !mask(y, x))
80 __host__ void mergeC2(const Src1Ptr& src1, const Src2Ptr& src2, const GlobPtr<DstType>& dst, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
83 const dim3 grid(divUp(cols, block.x), divUp(rows, block.y));
85 mergeC2<<<grid, block, 0, stream>>>(src1, src2, dst, mask, rows, cols);
93 __global__ void mergeC3(const Src1Ptr src1, const Src2Ptr src2, const Src3Ptr src3, GlobPtr<DstType> dst, const MaskPtr mask, const int rows, const int cols)
100 if (x >= cols || y >= rows || !mask(y, x))
111 __host__ void mergeC3(const Src1Ptr& src1, const Src2Ptr& src2, const Src3Ptr& src3, const GlobPtr<DstType>& dst, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
114 const dim3 grid(divUp(cols, block.x), divUp(rows, block.y));
116 mergeC3<<<grid, block, 0, stream>>>(src1, src2, src3, dst, mask, rows, cols)
162 mergeC2<Policy>(get<0>(src), get<1>(src), dst, mask, rows, cols, stream); local
171 mergeC3<Policy>(get<0>(src), get<1>(src), get<2>(src), dst, mask, rows, cols, stream); local
180 mergeC4<Policy>(get<0>(src), get<1>(src), get<2>(src), get<3>(src), dst, mask, rows, cols, stream); local
[all...] |
| /external/chromium-trace/catapult/tracing/tracing/ui/analysis/ |
| single_flow_event_sub_view.html | 21 var rows = this.__proto__.__proto__.getEventRows_(event);
24 rows.splice(0, 0, {
38 rows.push({
42 rows.push({
46 return rows;
|
| /external/eigen/blas/ |
| GeneralRank1Update.h | 22 static void run(Index rows, Index cols, Scalar* mat, Index stride, const Scalar* u, const Scalar* v, Scalar alpha)
29 Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i,rows) += alpha * cj(v[i]) * ConjRhsType(OtherMap(u,rows));
36 static void run(Index rows, Index cols, Scalar* mat, Index stride, const Scalar* u, const Scalar* v, Scalar alpha)
38 general_rank1_update<Scalar,Index,ColMajor,ConjRhs,ConjRhs>::run(rows,cols,mat,stride,u,v,alpha);
|
