| /external/libvpx/libvpx/test/ |
| vp9_subtract_test.cc | 22 typedef void (*SubtractFunc)(int rows, int cols, int16_t *diff_ptr,
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| /external/libvpx/libvpx/vpx_dsp/mips/ |
| subtract_msa.c | 229 void vpx_subtract_block_msa(int32_t rows, int32_t cols, int16_t *diff_ptr,
233 if (rows == cols) {
256 vpx_subtract_block_c(rows, cols, diff_ptr, diff_stride, src_ptr,
261 vpx_subtract_block_c(rows, cols, diff_ptr, diff_stride, src_ptr, src_stride,
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| /external/libvpx/libvpx/vpx_dsp/x86/ |
| subtract_sse2.asm | 15 ; void vpx_subtract_block(int rows, int cols,
22 rows, cols, diff, diff_stride, src, src_stride, \
|
| /external/opencv/cv/src/ |
| _cvmatrix.h | 49 #define icvSetZero_32f( dst, cols, rows ) memset((dst),0,(rows)*(cols)*sizeof(float))
51 #define icvSetZero_64d( dst, cols, rows ) memset((dst),0,(rows)*(cols)*sizeof(double))
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| cvcondens.cpp | 249 if( (lowerBound->cols != 1) || (upperBound->cols != 1) )
|
| cvconvhull.cpp | 296 if( (mat->cols != 1 && mat->rows != 1) || !CV_IS_MAT_CONT(mat->type))
300 if( mat->cols + mat->rows - 1 < ptseq->total )
311 mat->cols + mat->rows - 1, &hull_header.s, &hullblock ));
489 if( mat->rows > mat->cols )
492 mat->cols = hullseq->total;
578 if( (mat->cols != 1 && mat->rows != 1) ||
583 if( mat->cols + mat->rows - 1 > ptseq->total )
589 mat->cols + mat->rows - 1, &hull_header.s, &hullblock ));
|
| cvfeatureselect.cpp | 98 CV_CALL( _eigImg = cvCreateMat( img->rows, img->cols, CV_32FC1 ));
108 CV_CALL( _tmpImg = cvCreateMat( img->rows, img->cols, CV_32FC1 ));
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| /external/opencv/cvaux/src/ |
| cvbgfg_common.cpp | 92 double q = (mask->rows + mask->cols)/perimScale; // calculate perimeter len threshold
|
| /external/toybox/lib/ |
| lib.h | 260 int crunch_escape(FILE *out, int cols, int wc);
261 int crunch_rev_escape(FILE *out, int cols, int wc);
263 int (*escout)(FILE *out, int cols, int wc));
268 int (*escout)(FILE *out, int cols,int wc));
|
| /external/toolchain-utils/cros_utils/ |
| pstat.py | 57 recode (inlist,listmap,cols='all')
592 def recode(inlist, listmap, cols=None):
595 you need to recode data from (e.g.) strings to numbers. cols defaults
598 Usage: recode (inlist,listmap,cols=None) cols=recode cols, listmap=2D list
602 if cols != None:
603 if type(cols) not in [ListType, TupleType]:
604 cols = [cols]
[all...] |
| /external/opencv/ml/src/ |
| mlem.cpp | 161 p->cols != params.nclusters )
173 m->cols != train_data.dims )
184 w->rows != 1 && w->cols != 1 ||
185 w->rows + w->cols - 1 != params.nclusters )
197 cov->rows != cov->cols || cov->cols != train_data.dims )
226 dims = means->cols;
286 if( _probs->cols == 1 )
333 labels->cols != 1 && labels->rows != 1 || labels->cols + labels->rows - 1 != nsamples )
[all...] |
| /external/eigen/Eigen/src/Core/products/ |
| GeneralMatrixVector.h | 80 Index rows, Index cols,
89 Index rows, Index cols,
170 skipColumns = (std::min)(skipColumns,cols);
175 || (skipColumns + columnsAtOnce >= cols)
189 Index columnBound = ((cols-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
284 Index end = cols;
356 Index rows, Index cols,
365 Index rows, Index cols,
394 const Index depth = cols;
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| SelfadjointProduct.h | 100 Index size = mat.cols();
101 Index depth = actualOther.cols();
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| /external/eigen/Eigen/src/Eigenvalues/ |
| SelfAdjointEigenSolver.h | 163 : m_eivec(matrix.rows(), matrix.cols()),
164 m_eivalues(matrix.cols()),
407 eigen_assert(matrix.cols() == matrix.rows());
412 Index n = matrix.cols();
628 eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows());
735 eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
[all...] |
| /external/eigen/Eigen/src/IterativeLinearSolvers/ |
| ConjugateGradient.h | 41 Index n = mat.cols();
216 for(Index j=0; j<b.cols(); ++j)
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| /external/eigen/Eigen/src/SparseCore/ |
| SparseView.h | 59 inline Index cols() const { return m_matrix.cols(); } function in class:Eigen::SparseView
|
| /external/eigen/Eigen/src/SparseLU/ |
| SparseLU_SupernodalMatrix.h | 83 Index cols() { return m_col; } function in class:Eigen::internal::MappedSuperNodalMatrix
238 // eigen_assert(X.cols() <= NumTraits<Index>::highest());
240 Index nrhs = Index(X.cols());
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| SparseLU_kernel_bmod.h | 73 internal::sparselu_gemm<Scalar>(l.rows(), l.cols(), B.cols(), B.data(), B.outerStride(), u.data(), u.outerStride(), l.data(), l.outerStride());
|
| SparseLU_panel_bmod.h | 152 internal::sparselu_gemm<Scalar>(L.rows(), L.cols(), B.cols(), B.data(), B.outerStride(), U.data(), U.outerStride(), L.data(), L.outerStride());
|
| /external/eigen/test/ |
| main.h | 555 void createRandomPIMatrixOfRank(Index desired_rank, Index rows, Index cols, MatrixType& m);
557 void createRandomPIMatrixOfRank(Index desired_rank, Index rows, Index cols, MatrixType& m)
560 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
564 typedef Matrix<Scalar, Cols, Cols> MatrixBType;
568 m.setZero(rows,cols);
575 m = VectorType::Random(rows).normalized() * VectorType::Random(cols).normalized().transpose();
580 MatrixType d = MatrixType::Identity(rows,cols);
581 MatrixBType b = MatrixBType::Random(cols,cols);
[all...] |
| sparse_vector.cpp | 12 template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
14 double densityMat = (std::max)(8./(rows*cols), 0.01);
|
| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| MINRES.h | 52 const Index N(mat.cols()); // the size of the matrix
260 for(int j=0; j<b.cols(); ++j)
|
| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| LMqrsolv.h | 22 template <typename Scalar,int Rows, int Cols, typename PermIndex>
24 Matrix<Scalar,Rows,Cols> &s,
34 Index n = s.cols();
114 Index n = s.cols();
|
| /external/mesa3d/src/mesa/main/ |
| uniform_query.cpp | 473 unsigned rows, unsigned cols, unsigned count,
481 const unsigned elems = rows * cols * count;
482 const char *const extra = (cols == 1) ? "uniform" : "uniform matrix";
909 * Note: cols=2, rows=4 ==> array[2] of vec4
913 GLuint cols, GLuint rows,
945 if (vectors != cols || components != rows) {
981 cols, rows, uni->name, location,
[all...] |
| /external/python/cpython2/Demo/curses/ |
| ncurses.py | 32 def mkpanel(color, rows, cols, tly, tlx):
33 win = curses.newwin(rows, cols, tly, tlx)
76 for x in range(0, curses.COLS):
81 curses.COLS // 8 + 1,
88 curses.COLS // 7,
90 curses.COLS // 10)
95 curses.COLS // 10,
97 curses.COLS // 9)
102 curses.COLS // 8,
104 curses.COLS // 3
[all...] |
