| /external/eigen/Eigen/src/Core/ |
| PlainObjectBase.h | 38 static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
43 bool error = (rows == 0 || cols == 0) ? false
44 : (rows > max_index / cols);
136 EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); } function in class:Eigen::PlainObjectBase
141 return m_storage.data()[colId + rowId * m_storage.cols()];
154 return m_storage.data()[colId + rowId * m_storage.cols()];
167 return m_storage.data()[colId + rowId * m_storage.cols()];
183 ? colId + rowId * m_storage.cols()
200 ? colId + rowId * m_storage.cols()
[all...] |
| EigenBase.h | 43 /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
46 inline Index cols() const { return derived().cols(); } function in struct:Eigen::EigenBase
47 /** \returns the number of coefficients, which is rows()*cols().
48 * \sa rows(), cols(), SizeAtCompileTime. */
49 inline Index size() const { return rows() * cols(); }
60 typename Dest::PlainObject res(rows(),cols());
70 typename Dest::PlainObject res(rows(),cols());
|
| /external/eigen/Eigen/src/LU/ |
| FullPivLU.h | 80 FullPivLU(Index rows, Index cols);
315 return cols() - rank();
328 return rank() == cols();
353 return isInjective() && (m_lu.rows() == m_lu.cols());
366 eigen_assert(m_lu.rows() == m_lu.cols() && "You can't take the inverse of a non-square matrix!");
368 (*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()));
374 inline Index cols() const { return m_lu.cols(); } function in class:Eigen::FullPivLU
394 FullPivLU<MatrixType>::FullPivLU(Index rows, Index cols)
395 : m_lu(rows, cols),
429 const Index cols = matrix.cols(); local
556 const Index cols = dec().matrixLU().cols(), dimker = cols - rank(); local
682 const Index rows = dec().rows(), cols = dec().cols(), local
[all...] |
| /external/compiler-rt/lib/sanitizer_common/scripts/ |
| gen_dynamic_list.py | 42 cols = line.split(' ')
43 if (len(cols) == 3 and cols[1] in ('T', 'W')) :
44 functions.append(cols[2])
|
| /external/eigen/bench/ |
| basicbenchmark.h | 44 const int cols = mat.cols(); local
46 MatrixType I(rows,cols);
47 MatrixType m(rows,cols);
|
| sparse_dense_product.cpp | 55 int cols = SIZE; local
58 EigenSparseMatrix sm1(rows,cols);
59 DenseVector v1(cols), v2(cols);
65 //fillMatrix(density, rows, cols, sm1);
66 fillMatrix2(7, rows, cols, sm1);
72 DenseMatrix m1(rows,cols);
93 std::cout << "Eigen sparse\t" << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
106 // std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/float(m1.rows()*m1.cols())*100 << "%\n";
119 //GmmDynSparse gmmT3(rows,cols);
[all...] |
| sparse_cholesky.cpp | 44 void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix& dst)
46 dst.startFill(rows*cols*density);
47 for(int j = 0; j < cols; j++)
80 int cols = SIZE; local
84 VectorXf b = VectorXf::Random(cols);
85 VectorXf x = VectorXf::Random(cols);
92 EigenSparseSelfAdjointMatrix sm1(rows, cols);
94 fillSpdMatrix(density, rows, cols, sm1);
103 DenseMatrix m1(rows,cols);
117 for (int j=0; j<cols; ++j
[all...] |
| sparse_lu.cpp | 75 int cols = SIZE; local
79 VectorX b = VectorX::Random(cols);
80 VectorX x = VectorX::Random(cols);
87 EigenSparseMatrix sm1(rows, cols);
88 fillMatrix(density, rows, cols, sm1);
96 DenseMatrix m1(rows,cols);
|
| /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)
28 for (Index i=0; i<cols; ++i)
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);
|
| /external/eigen/doc/examples/ |
| function_taking_eigenbase.cpp | 8 std::cout << "size (rows, cols): " << b.size() << " (" << b.rows()
9 << ", " << b.cols() << ")" << std::endl;
|
| /external/eigen/test/ |
| diagonalmatrices.cpp | 16 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
18 typedef Matrix<Scalar, 1, Cols> RowVectorType;
21 typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
22 typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
24 Index cols = m.cols(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols);
30 RowVectorType rv1 = RowVectorType::Random(cols),
[all...] |
| selfadjoint.cpp | 21 Index cols = m.cols(); local
23 MatrixType m1 = MatrixType::Random(rows, cols),
24 m3(rows, cols);
|
| sizeoverflow.cpp | 24 void triggerMatrixBadAlloc(Index rows, Index cols)
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.
|
| 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) * s1, m1 * s1)
[all...] |
| product_selfadjoint.cpp | 22 Index cols = m.cols(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m2 = MatrixType::Random(rows, cols),
56 m2.block(1,1,rows-1,cols-1).template selfadjointView<Lower>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
58 m3.block(1,1,rows-1,cols-1) += v1.tail(rows-1) * v2.head(cols-1).adjoint()+ v2.head(cols-1) * v1.tail(rows-1).adjoint();
|
| 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) );
|
| /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_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);
|
| /external/opencv/cvaux/src/ |
| cvvideo.cpp | 64 if( frame->cols != even->cols || frame->cols != odd->cols ||
|
| /external/ceres-solver/internal/ceres/ |
| 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)
[all...] |
| 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)
[all...] |
| /external/eigen/Eigen/src/Core/products/ |
| GeneralMatrixVector_MKL.h | 57 Index rows, Index cols, \
64 rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
67 rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
74 Index rows, Index cols, \
80 rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
96 Index rows, Index cols, \
101 MKL_INT m=rows, n=cols, lda=lhsStride, incx=rhsIncr, incy=resIncr; \
106 m=cols; \
113 Map<const GEMVVector, 0, InnerStride<> > map_x(rhs,cols,1,InnerStride<>(incx)); \
|
| /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
[all...] |
| /external/chromium_org/third_party/libvpx/source/libvpx/vp9/encoder/arm/neon/ |
| vp9_subtract_neon.c | 17 void vp9_subtract_block_neon(int rows, int cols,
23 if (cols > 16) {
25 for (c = 0; c < cols; c += 32) {
47 } else if (cols > 8) {
61 } else if (cols > 4) {
73 for (c = 0; c < cols; ++c)
|
| /external/eigen/Eigen/src/QR/ |
| ColPivHouseholderQR_MKL.h | 55 Index cols = matrix.cols();\
61 m_colsTranspositions.resize(cols);\
66 m_colsPermutation.resize(cols); \
71 LAPACKE_##MKLPREFIX##geqp3( matrix_order, rows, cols, (MKLTYPE*)m_qr.data(), lda, (lapack_int*)m_colsPermutation.indices().data(), (MKLTYPE*)m_hCoeffs.data()); \
80 for(i=0;i<cols;i++) perm[i]--;\
|
