| /external/deqp/framework/common/ |
| D | tcuMatrix.hpp | 34 template <typename T, int Rows, int Cols>
38 typedef Vector<T, Rows> Element;
44 ROWS = Rows, enumerator
50 explicit Matrix (const T src[Rows*Cols]);
51 Matrix (const Vector<T, Rows>& src);
52 Matrix (const Matrix<T, Rows, Cols>& src);
55 Matrix<T, Rows, Cols>& operator= (const Matrix<T, Rows, Cols>& src);
56 Matrix<T, Rows, Cols>& operator*= (const Matrix<T, Rows, Cols>& src);
59 void setColumn (int colNdx, const Vector<T, Rows>& vec);
62 Vector<T, Rows>& getColumn (int ndx);
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| /external/eigen/test/ |
| D | sparse_basic.cpp | 19 const Index rows = ref.rows(); in sparse_basic() local
24 double density = (std::max)(8./(rows*cols), 0.01); in sparse_basic()
32 SparseMatrixType m(rows, cols); in sparse_basic()
33 DenseMatrix refMat = DenseMatrix::Zero(rows, cols); in sparse_basic()
34 DenseVector vec1 = DenseVector::Random(rows); in sparse_basic()
61 int i = internal::random<int>(0,rows-1); in sparse_basic()
63 int h = internal::random<int>(1,rows-i-1); in sparse_basic()
121 for(int r=0; r<rows; r++) in sparse_basic()
135 DenseMatrix m1(rows,cols); in sparse_basic()
137 SparseMatrixType m2(rows,cols); in sparse_basic()
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| D | array.cpp | 19 Index rows = m.rows(); in array() local
22 ArrayType m1 = ArrayType::Random(rows, cols), in array()
23 m2 = ArrayType::Random(rows, cols), in array()
24 m3(rows, cols); in array()
26 ColVectorType cv1 = ColVectorType::Random(rows); in array()
34 VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1); in array()
36 VERIFY_IS_APPROX(m1 - s1, m1 - ArrayType::Constant(rows,cols,s1)); in array()
37 VERIFY_IS_APPROX(s1 - m1, ArrayType::Constant(rows,cols,s1) - m1); in array()
38 VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - ArrayType::Constant(rows,cols,s2) ); in array()
48 …ArrayType::Map(m1.data(), m1.rows(), m1.cols()) -= ArrayType::Map(m2.data(), m2.rows(), m2.cols()); in array()
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| D | array_for_matrix.cpp | 19 Index rows = m.rows(); in array_for_matrix() local
22 MatrixType m1 = MatrixType::Random(rows, cols), in array_for_matrix()
23 m2 = MatrixType::Random(rows, cols), in array_for_matrix()
24 m3(rows, cols); in array_for_matrix()
26 ColVectorType cv1 = ColVectorType::Random(rows); in array_for_matrix()
34 VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1); in array_for_matrix()
35 …VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,… in array_for_matrix()
62 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().prod(), ColVectorType::Ones(rows)); in array_for_matrix()
80 Index rows = m.rows(); in comparisons() local
83 Index r = internal::random<Index>(0, rows-1), in comparisons()
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| D | sparse_product.cpp | 27 Index r = internal::random<Index>(0,m2.rows()-1); in run()
42 const Index rows = internal::random<Index>(1,n); in sparse_product() local
48 double density = (std::max)(8./(rows*cols), 0.1); in sparse_product()
60 DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth); in sparse_product()
61 DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows); in sparse_product()
64 DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols); in sparse_product()
65 DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows); in sparse_product()
67 DenseMatrix refMat6 = DenseMatrix::Random(rows, rows); in sparse_product()
68 DenseMatrix dm4 = DenseMatrix::Zero(rows, rows); in sparse_product()
69 // DenseVector dv1 = DenseVector::Random(rows); in sparse_product()
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| D | diagonalmatrices.cpp | 16 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; in diagonalmatrices() enumerator
17 typedef Matrix<Scalar, Rows, 1> VectorType; in diagonalmatrices()
19 typedef Matrix<Scalar, Rows, Rows> SquareMatrixType; in diagonalmatrices()
20 typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix; in diagonalmatrices()
22 typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix; in diagonalmatrices()
23 Index rows = m.rows(); in diagonalmatrices() local
26 MatrixType m1 = MatrixType::Random(rows, cols), in diagonalmatrices()
27 m2 = MatrixType::Random(rows, cols); in diagonalmatrices()
28 VectorType v1 = VectorType::Random(rows), in diagonalmatrices()
29 v2 = VectorType::Random(rows); in diagonalmatrices()
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| D | householder.cpp | 21 Index rows = m.rows(); in householder() local
34 …E_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp((std::max)(rows,cols)); in householder()
41 VectorType v1 = VectorType::Random(rows), v2; in householder()
46 if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(v1.tail(rows-1).norm(), v1.norm()); in householder()
47 v1 = VectorType::Random(rows); in householder()
52 MatrixType m1(rows, cols), in householder()
53 m2(rows, cols); in householder()
55 v1 = VectorType::Random(rows); in householder()
56 if(even) v1.tail(rows-1).setZero(); in householder()
62 if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(m1.block(1,0,rows-1,cols).norm(), m1.norm()); in householder()
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| /external/eigen/test/eigen2/ |
| D | eigen2_sparse_product.cpp | 14 const int rows = ref.rows(); in sparse_product() local
19 double density = std::max(8./(rows*cols), 0.01); in sparse_product()
25 DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); in sparse_product()
26 DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows); in sparse_product()
27 DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows); in sparse_product()
28 DenseMatrix dm4 = DenseMatrix::Zero(rows, rows); in sparse_product()
29 SparseMatrixType m2(rows, rows); in sparse_product()
30 SparseMatrixType m3(rows, rows); in sparse_product()
31 SparseMatrixType m4(rows, rows); in sparse_product()
58 DenseMatrix refM2 = DenseMatrix::Zero(rows, rows); in sparse_product()
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| D | eigen2_sparse_basic.cpp | 48 const int rows = ref.rows(); in sparse_basic() local
53 double density = std::max(8./(rows*cols), 0.01); in sparse_basic()
58 SparseMatrixType m(rows, cols); in sparse_basic()
59 DenseMatrix refMat = DenseMatrix::Zero(rows, cols); in sparse_basic()
60 DenseVector vec1 = DenseVector::Random(rows); in sparse_basic()
88 int i = ei_random<int>(0,rows-1); in sparse_basic()
90 int h = ei_random<int>(1,rows-i-1); in sparse_basic()
117 for(int r=0; r<rows; r++) in sparse_basic()
167 DenseMatrix m1(rows,cols); in sparse_basic()
169 SparseMatrixType m2(rows,cols); in sparse_basic()
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| /external/opencv3/modules/cudev/include/opencv2/cudev/grid/ |
| D | split_merge.hpp | 68 const int rows = getRows(src); in gridMerge_() local
71 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridMerge_()
73 dst.create(rows, cols); in gridMerge_()
78 rows, cols, in gridMerge_()
87 const int rows = getRows(src); in gridMerge_() local
90 CV_Assert( getRows(dst) == rows && getCols(dst) == cols ); in gridMerge_()
91 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridMerge_()
96 rows, cols, in gridMerge_()
105 const int rows = getRows(src); in gridMerge_() local
108 dst.create(rows, cols); in gridMerge_()
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| D | transform.hpp | 66 const int rows = getRows(src); in gridTransformUnary_() local
69 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridTransformUnary_()
71 dst.create(rows, cols); in gridTransformUnary_()
73 …nsform_unary<Policy>(shrinkPtr(src), shrinkPtr(dst), op, shrinkPtr(mask), rows, cols, StreamAccess… in gridTransformUnary_()
79 const int rows = getRows(src); in gridTransformUnary_() local
82 CV_Assert( getRows(dst) == rows && getCols(dst) == cols ); in gridTransformUnary_()
83 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridTransformUnary_()
85 …nsform_unary<Policy>(shrinkPtr(src), shrinkPtr(dst), op, shrinkPtr(mask), rows, cols, StreamAccess… in gridTransformUnary_()
91 const int rows = getRows(src); in gridTransformUnary_() local
94 dst.create(rows, cols); in gridTransformUnary_()
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| D | copy.hpp | 66 const int rows = getRows(src); in gridCopy_() local
69 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridCopy_()
71 dst.create(rows, cols); in gridCopy_()
73 …grid_copy_detail::copy<Policy>(shrinkPtr(src), shrinkPtr(dst), shrinkPtr(mask), rows, cols, Stream… in gridCopy_()
79 const int rows = getRows(src); in gridCopy_() local
82 CV_Assert( getRows(dst) == rows && getCols(dst) == cols ); in gridCopy_()
83 CV_Assert( getRows(mask) == rows && getCols(mask) == cols ); in gridCopy_()
85 …grid_copy_detail::copy<Policy>(shrinkPtr(src), shrinkPtr(dst), shrinkPtr(mask), rows, cols, Stream… in gridCopy_()
91 const int rows = getRows(src); in gridCopy_() local
94 dst.create(rows, cols); in gridCopy_()
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| /external/llvm/include/llvm/CodeGen/PBQP/ |
| D | Math.h | 169 Matrix(unsigned Rows, unsigned Cols) : in Matrix() argument
170 Rows(Rows), Cols(Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix()
175 Matrix(unsigned Rows, unsigned Cols, PBQPNum InitVal) in Matrix() argument
176 : Rows(Rows), Cols(Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix()
177 std::fill(Data, Data + (Rows * Cols), InitVal); in Matrix()
182 : Rows(M.Rows), Cols(M.Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix()
183 std::copy(M.Data, M.Data + (Rows * Cols), Data); in Matrix()
188 : Rows(M.Rows), Cols(M.Cols), Data(M.Data) { in Matrix()
189 M.Rows = M.Cols = 0; in Matrix()
199 Rows = M.Rows; Cols = M.Cols;
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| /external/chromium-trace/catapult/tracing/tracing/ui/analysis/ |
| D | counter_sample_sub_view_test.html | 43 var rows = analysisEl.$.table.tableRows;
44 assert.lengthOf(rows, 1);
45 assert.isTrue(rows[0].isExpanded);
46 assert.equal(rows[0].counter, 'ctr1');
47 assert.equal(rows[0].series, 'series1');
48 assert.equal(rows[0].start, 0);
49 assert.equal(rows[0].value, 0);
52 var subRows = rows[0].subRows;
73 var rows = analysisEl.$.table.tableRows;
74 assert.lengthOf(rows, 1);
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| D | single_event_sub_view.html | 71 var rows = [];
74 rows.push({ name: 'Error', value: event.error });
77 rows.push({ name: 'Title', value: event.title });
80 rows.push({ name: 'Category', value: event.category });
85 rows.push({ name: 'User Friendly Category', value: ufc });
89 rows.push({ name: 'Name', value: event.name });
91 rows.push({
99 rows.push({
108 rows.push({
118 rows.push({
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| /external/opencv3/modules/video/src/opencl/ |
| D | optical_flow_farneback.cl | 74 const int rows, const int cols,
87 if (y < rows && y >= 0)
99 float t1 = src[mad24(min(y + k, rows - 1), srcStep, xWarped)];
109 if (y < rows && y >= 0 && tx >= polyN && tx + polyN < bdx && x < cols)
128 dst[mad24(rows + y, dstStep, xWarped)] = (float)(b2*ig.s0);
129 dst[mad24(2*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b5*ig.s2);
130 dst[mad24(3*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b4*ig.s2);
131 dst[mad24(4*rows + y, dstStep, xWarped)] = (float)(b6*ig.s3);
161 __global float * dst, int dstStep, const int rows, const int cols,
170 if (y < rows)
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| /external/eigen/doc/ |
| D | 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)
39 C.setZero(rows,cols) // C = ones(rows,cols)
40 MatrixXd::Ones(rows,cols) // ones(rows,cols)
41 C.setOnes(rows,cols) // C = ones(rows,cols)
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| /external/eigen/unsupported/Eigen/src/MatrixFunctions/ |
| D | MatrixLogarithm.h | 85 MatrixType result(A.rows(), A.rows()); in compute()
86 if (A.rows() == 1) in compute()
88 else if (A.rows() == 2) in compute()
140 …RealScalar normTminusI = (T - MatrixType::Identity(T.rows(), T.rows())).cwiseAbs().colwise().sum()… in computeBig()
241 MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); in computePade3()
242 result.setZero(T.rows(), T.rows()); in computePade3()
244 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) in computePade3()
257 MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); in computePade4()
258 result.setZero(T.rows(), T.rows()); in computePade4()
260 result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) in computePade4()
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| /external/libvpx/libvpx/third_party/libyuv/source/ |
| D | convert_jpeg.cc | 37 int rows) { in JpegCopyI420() argument
45 dest->w, rows); in JpegCopyI420()
46 dest->y += rows * dest->y_stride; in JpegCopyI420()
47 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegCopyI420()
48 dest->v += ((rows + 1) >> 1) * dest->v_stride; in JpegCopyI420()
49 dest->h -= rows; in JpegCopyI420()
55 int rows) { in JpegI422ToI420() argument
63 dest->w, rows); in JpegI422ToI420()
64 dest->y += rows * dest->y_stride; in JpegI422ToI420()
65 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegI422ToI420()
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| /external/opencv3/modules/core/src/ |
| D | cuda_gpu_mat.cpp | 50 flags(Mat::MAGIC_VAL + (type_ & Mat::TYPE_MASK)), rows(rows_), cols(cols_), in GpuMat()
64 if (rows == 1) in GpuMat()
72 dataend += step * (rows - 1) + minstep; in GpuMat()
76 flags(Mat::MAGIC_VAL + (type_ & Mat::TYPE_MASK)), rows(size_.height), cols(size_.width), in GpuMat()
90 if (rows == 1) in GpuMat()
98 dataend += step * (rows - 1) + minstep; in GpuMat()
110 rows = m.rows; in GpuMat()
114 … CV_Assert( 0 <= rowRange_.start && rowRange_.start <= rowRange_.end && rowRange_.end <= m.rows ); in GpuMat()
116 rows = rowRange_.size(); in GpuMat()
133 if (rows == 1) in GpuMat()
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| /external/gemmlowp/meta/generators/ |
| D | gemm_NxMxK_neon.py | 41 def GenerateCommonTempsCountersAndConsts(emitter, rows): argument
56 if rows is not 0:
58 'std::int32_t*', 'zipped_lhs_%d_offsets' % rows,
59 'reinterpret_cast<std::int32_t*>(zipped_lhs + padded_k * %d)' % rows)
68 def GenerateQuantized8BitTempsCountersAndConsts(emitter, rows): argument
70 GenerateCommonTempsCountersAndConsts(emitter, rows)
85 def GenerateFullTempsCountersAndConsts(emitter, result_type, rows): argument
87 GenerateCommonTempsCountersAndConsts(emitter, rows)
97 def ZipName(rows, leftovers, aligned): argument
98 return zip_Nx8_neon.BuildName(rows, leftovers, aligned)
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| /external/eigen/Eigen/src/Core/ |
| D | 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);
135 EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
143 return m_storage.data()[rowId + colId * m_storage.rows()];
156 return m_storage.data()[rowId + colId * m_storage.rows()];
169 return m_storage.data()[rowId + colId * m_storage.rows()];
184 : rowId + colId * m_storage.rows()));
201 : rowId + colId * m_storage.rows()), val);
219 /** Resizes \c *this to a \a rows x \a cols matrix.
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| /external/chromium-trace/catapult/tracing/tracing/ui/base/ |
| D | table_test.html | 46 // body rows).
83 // body rows).
104 var rows = [
117 table.tableRows = rows;
140 var rows = [
163 table.tableRows = rows;
187 var rows = [
224 table.tableRows = rows;
251 var rows = [
323 table.tableRows = rows;
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| /external/opencv3/modules/cudaarithm/test/ |
| D | test_arithm.cpp | 201 void testC2C(const std::string& hint, int cols, int rows, int flags, bool inplace) in testC2C() argument
205 cv::Mat a = randomMat(cv::Size(cols, rows), CV_32FC2, 0.0, 10.0); in testC2C()
215 … d_b = cv::cuda::GpuMat(a.rows, a.cols, CV_32FC2, d_b_data.ptr(), a.cols * d_b_data.elemSize()); in testC2C()
217 cv::cuda::dft(loadMat(a), d_b, cv::Size(cols, rows), flags); in testC2C()
222 EXPECT_MAT_NEAR(b_gold, cv::Mat(d_b), rows * cols * 1e-4); in testC2C()
229 int rows = randomInt(2, 100); in CUDA_TEST_P() local
235 testC2C("no flags", cols, rows, 0, inplace); in CUDA_TEST_P()
236 testC2C("no flags 0 1", cols, rows + 1, 0, inplace); in CUDA_TEST_P()
237 testC2C("no flags 1 0", cols, rows + 1, 0, inplace); in CUDA_TEST_P()
238 testC2C("no flags 1 1", cols + 1, rows, 0, inplace); in CUDA_TEST_P()
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| /external/opencv3/modules/cudabgsegm/src/cuda/ |
| D | mog.cu | 125 if (x >= frame.cols || y >= frame.rows) in mog_withoutLearning()
135 if (gmm_weight(k * frame.rows + y, x) < numeric_limits<float>::epsilon()) in mog_withoutLearning()
138 WorkT mu = gmm_mean(k * frame.rows + y, x); in mog_withoutLearning()
139 WorkT var = gmm_var(k * frame.rows + y, x); in mog_withoutLearning()
155 wsum += gmm_weight(k * frame.rows + y, x); in mog_withoutLearning()
173 dim3 grid(divUp(frame.cols, block.x), divUp(frame.rows, block.y)); in mog_withoutLearning_caller()
202 if (x >= frame.cols || y >= frame.rows) in mog_withLearning()
214 float w = gmm_weight(k * frame.rows + y, x); in mog_withLearning()
220 WorkT mu = gmm_mean(k * frame.rows + y, x); in mog_withLearning()
221 WorkT var = gmm_var(k * frame.rows + y, x); in mog_withLearning()
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