| /external/eigen/test/ |
| basicstuff.cpp | 22 Index 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),
39 c = internal::random<Index>(0, cols-1);
71 VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows,cols)(r,c), static_cast<Scalar>(1));
82 if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
84 VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)))
140 Index cols = m.cols(); local
[all...] |
| selfadjoint.cpp | 22 Index cols = m.cols(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m3(rows, cols);
|
| 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, cols);
[all...] |
| block.cpp | 24 Index cols = m.cols(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
28 m2 = MatrixType::Random(rows, cols),
29 m3(rows, cols),
30 ones = MatrixType::Ones(rows, cols);
37 Index c1 = internal::random<Index>(0,cols-1);
38 Index c2 = internal::random<Index>(c1,cols-1);
58 RowVectorType br1(m1.block(r1,0,1,cols));
71 if (rows>=5 && cols>=8
155 Index cols = m.cols(); local
189 Index cols = m.cols(); local
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| cwiseop.cpp | 39 Index cols = m.cols(); local
41 MatrixType m1 = MatrixType::Random(rows, cols),
42 m2 = MatrixType::Random(rows, cols),
43 m3(rows, cols),
44 m4(rows, cols),
45 mzero = MatrixType::Zero(rows, cols),
46 mones = MatrixType::Ones(rows, cols),
54 c = internal::random<Index>(0, cols-1);
59 m3 = MatrixType::Constant(rows, cols, s1)
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| 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);
28 VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
39 for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
45 MatrixType m2 = MatrixType::Random(cols,cols2);
47 m2 = MatrixType::Random(cols,cols2);
|
| sparse_basic.cpp | 18 const Index cols = ref.cols(); local
22 double density = (std::max)(8./(rows*cols), 0.01);
27 SparseMatrixType m(rows, cols);
28 DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
56 int j = internal::random<int>(0,cols-1);
58 int w = internal::random<int>(1,cols-j-1);
80 for(int c=0; c<cols; c++)
95 DenseMatrix m1(rows,cols);
97 SparseMatrixType m2(rows,cols);
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| /external/eigen/test/eigen2/ |
| eigen2_submatrices.cpp | 22 int cols = m1.cols(); local
25 VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1));
49 int cols = m.cols(); local
51 MatrixType m1 = MatrixType::Random(rows, cols),
52 m2 = MatrixType::Random(rows, cols),
53 m3(rows, cols),
54 mzero = MatrixType::Zero(rows, cols),
55 ones = MatrixType::Ones(rows, cols),
[all...] |
| 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);
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| eigen2_triangular.cpp | 21 int cols = m.cols(); 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, cols),
[all...] |
| eigen2_cwiseop.cpp | 29 int cols = m.cols(); local
31 MatrixType m1 = MatrixType::Random(rows, cols),
32 m2 = MatrixType::Random(rows, cols),
33 m3(rows, cols),
34 m4(rows, cols),
35 mzero = MatrixType::Zero(rows, cols),
36 mones = MatrixType::Ones(rows, cols),
47 c = ei_random<int>(0, cols-1);
52 m3 = MatrixType::Constant(rows, cols, s1)
[all...] |
| eigen2_adjoint.cpp | 23 int cols = m.cols(); local
29 MatrixType m1 = MatrixType::Random(rows, cols),
30 m2 = MatrixType::Random(rows, cols),
31 m3(rows, cols),
32 mzero = MatrixType::Zero(rows, cols),
68 c = ei_random<int>(0, cols-1);
|
| /external/skia/src/utils/ |
| SkBoundaryPatch.cpp | 44 bool SkBoundaryPatch::evalPatch(SkPoint verts[], int rows, int cols) {
45 if (rows < 2 || cols < 2) {
50 const SkScalar invC = SkScalarInvert(SkIntToScalar(cols - 1));
52 for (int y = 0; y < cols; y++) {
|
| /external/ceres-solver/internal/ceres/ |
| block_jacobi_preconditioner.cc | 49 for (int c = 0; c < block_structure_.cols.size(); ++c) {
50 int size = block_structure_.cols[c].size;
55 blocks_.resize(block_structure_.cols.size());
60 for (int c = 0; c < block_structure_.cols.size(); ++c) {
61 int size = block_structure_.cols[c].size;
80 const int col_block_size = bs->cols[cells[c].block_id].size;
103 for (int c = 0; c < bs->cols.size(); ++c) {
104 const int size = block_structure_.cols[c].size;
105 const int position = block_structure_.cols[c].position;
122 for (int c = 0; c < block_structure_.cols.size(); ++c)
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| incomplete_lq_factorization_test.cc | 52 EXPECT_EQ(expected.cols()[i], actual.cols()[i]);
85 int* cols = matrix.mutable_cols(); local
94 cols[idx] = j;
141 EXPECT_EQ(matrix.cols()[0], 0);
149 EXPECT_EQ(matrix.cols()[idx], idx - matrix.rows()[1]);
159 EXPECT_EQ(matrix.cols()[matrix.rows()[2]], 0);
160 EXPECT_EQ(matrix.cols()[matrix.rows()[2] + 1], 3);
161 EXPECT_EQ(matrix.cols()[matrix.rows()[2] + 2], 5);
173 EXPECT_EQ(matrix.cols()[matrix.rows()[3]], 0)
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| compressed_row_sparse_matrix.cc | 46 // duplicates in the pair of arrays rows and cols, i.e., there is no
49 // rows[i] == rows[j] && cols[i] == cols[j]
53 RowColLessThan(const int* rows, const int* cols)
54 : rows(rows), cols(cols) {
59 return (cols[x] < cols[y]);
65 const int* cols; member in struct:ceres::internal::__anon1302::RowColLessThan
106 sort(index.begin(), index.end(), RowColLessThan(m.rows(), m.cols()));
304 int* cols = matrix->mutable_cols(); local
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| triplet_sparse_matrix_test.cc | 81 EXPECT_EQ(m.cols()[0], 1);
82 EXPECT_EQ(m.cols()[1], 4);
122 EXPECT_EQ(cpy.cols()[0], 1);
123 EXPECT_EQ(cpy.cols()[1], 4);
168 EXPECT_EQ(cpy.cols()[0], 1);
169 EXPECT_EQ(cpy.cols()[1], 4);
221 EXPECT_EQ(m.cols()[0], 1);
222 EXPECT_EQ(m.cols()[1], 4);
223 EXPECT_EQ(m.cols()[2], 1);
224 EXPECT_EQ(m.cols()[3], 4)
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| /external/eigen/Eigen/src/SVD/ |
| UpperBidiagonalization.h | 56 : m_householder(matrix.rows(), matrix.cols()),
57 m_bidiagonal(matrix.cols(), matrix.cols()),
78 .setLength(m_householder.cols()-1)
92 Index cols = matrix.cols(); local
94 eigen_assert(rows >= cols && "UpperBidiagonalization is only for matrices satisfying rows>=cols.");
100 for (Index k = 0; /* breaks at k==cols-1 below */ ; ++k)
103 Index remainingCols = cols - k - 1
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| JacobiSVD.h | 79 if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
81 m_qr = FullPivHouseholderQR<MatrixType>(svd.rows(), svd.cols());
88 if(matrix.rows() > matrix.cols())
91 svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
122 if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
124 m_qr = FullPivHouseholderQR<TransposeTypeWithSameStorageOrder>(svd.cols(), svd.rows());
126 m_adjoint.resize(svd.cols(), svd.rows())
653 inline Index cols() const { return m_cols; } function in class:Eigen::JacobiSVD
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| /external/ceres-solver/include/ceres/ |
| crs_matrix.h | 48 // rows, cols and values.
50 // rows is a num_rows + 1 sized array that points into the cols and
53 // cols[rows[i]] ... cols[rows[i + 1] - 1] are the indices of the
59 // cols and values contain as many entries as there are non-zeros in
73 // cols = [ 1, 3, 1, 2, 3, 0, 1]
76 vector<int> cols; member in struct:ceres::CRSMatrix
|
| /external/eigen/Eigen/src/misc/ |
| SparseSolve.h | 39 inline Index rows() const { return m_dec.cols(); }
40 inline Index cols() const { return m_rhs.cols(); } function in struct:Eigen::internal::sparse_solve_retval_base
63 using Base::cols; \
92 inline Index rows() const { return m_dec.cols(); }
93 inline Index cols() const { return m_rhs.cols(); } function in struct:Eigen::internal::solve_retval_with_guess
|
| /external/libvpx/libvpx/examples/ |
| vp8_set_maps.txt | 36 roi.cols = cfg.g_w/16;
54 roi.roi_map = malloc(roi.rows * roi.cols);
55 for(i=0;i<roi.rows*roi.cols;i++)
67 active.cols = cfg.g_w/16;
70 active.active_map = malloc(active.rows * active.cols);
71 for(i=0;i<active.rows*active.cols;i++)
82 active.cols = cfg.g_w/16;
|
| /external/eigen/Eigen/src/Core/products/ |
| SelfadjointMatrixMatrix.h | 22 void pack(Scalar* blockA, const const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
42 for(Index k=i+BlockRows; k<cols; k++)
46 void operator()(Scalar* blockA, const Scalar* _lhs, Index lhsStride, Index cols, Index rows)
53 pack<Pack1>(blockA, lhs, cols, i, count);
58 pack<Pack2>(blockA, lhs, cols, peeled_mc, count);
70 for(Index k=i+1; k<cols; k++)
80 void operator()(Scalar* blockB, const Scalar* _rhs, Index rhsStride, Index rows, Index cols, Index k2)
85 Index packet_cols = (cols/nr)*nr;
166 for(Index j2=packet_cols; j2<cols; ++j2)
210 Index rows, Index cols,
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| /external/eigen/Eigen/src/LU/ |
| FullPivLU.h | 79 FullPivLU(Index rows, Index cols);
313 return cols() - rank();
326 return rank() == cols();
351 return isInjective() && (m_lu.rows() == m_lu.cols());
364 eigen_assert(m_lu.rows() == m_lu.cols() && "You can't take the inverse of a non-square matrix!");
366 (*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()));
372 inline Index cols() const { return m_lu.cols(); } function in class:Eigen::FullPivLU
392 FullPivLU<MatrixType>::FullPivLU(Index rows, Index cols)
393 : m_lu(rows, cols),
424 const Index cols = matrix.cols(); local
550 const Index cols = dec().matrixLU().cols(), dimker = cols - rank(); local
675 const Index rows = dec().rows(), cols = dec().cols(), local
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| /external/opencv/cv/src/ |
| cvtemplmatch.cpp | 103 if( img->cols < templ->cols || img->rows < templ->rows )
108 corr->cols > img->cols + templ->cols - 1 )
112 blocksize.width = cvRound(templ->cols*block_scale);
113 blocksize.width = MAX( blocksize.width, min_block_size - templ->cols + 1 );
114 blocksize.width = MIN( blocksize.width, corr->cols );
119 dftsize.width = cvGetOptimalDFTSize(blocksize.width + templ->cols - 1);
127 blocksize.width = dftsize.width - templ->cols + 1
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