/external/eigen/doc/examples/ |
H A D | function_taking_eigenbase.cpp | 8 std::cout << "size (rows, cols): " << b.size() << " (" << b.rows() 9 << ", " << b.cols() << ")" << std::endl;
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/external/eigen/test/ |
H A D | diagonalmatrices.cpp | 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), 31 rv2 = RowVectorType::Random(cols); 56 Index j = internal::random<Index>(0, cols-1); 69 big.setZero(2*rows, 2*cols); 71 big.block(i,j,rows,cols) = m1; 72 big.block(i,j,rows,cols) [all...] |
H A D | selfadjoint.cpp | 21 Index cols = m.cols(); local 23 MatrixType m1 = MatrixType::Random(rows, cols), 24 m3(rows, cols);
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H A D | sizeoverflow.cpp | 24 void triggerMatrixBadAlloc(Index rows, Index cols) argument 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.
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H A D | 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) * s [all...] |
H A D | conservative_resize.cpp | 41 const Index cols = internal::random<Index>(1,50); local 43 m.conservativeResize(rows,cols); 44 VERIFY_IS_APPROX(m, n.block(0,0,rows,cols)); 51 const Index cols = internal::random<Index>(50,75); local 53 m.conservativeResizeLike(MatrixType::Zero(rows,cols)); 54 VERIFY_IS_APPROX(m.block(0,0,n.rows(),n.cols()), n); 55 VERIFY( rows<=50 || m.block(50,0,rows-50,cols).sum() == Scalar(0) ); 56 VERIFY( cols<=50 || m.block(0,50,rows,cols-50).sum() == Scalar(0) );
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H A D | 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();
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H A D | 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) );
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/external/eigen/test/eigen2/ |
H A D | 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...] |
H A D | 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);
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/external/opencv/cvaux/src/ |
H A D | cvvideo.cpp | 64 if( frame->cols != even->cols || frame->cols != odd->cols ||
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/external/eigen/Eigen/src/misc/ |
H A D | Kernel.h | 27 // is the number of cols of the original matrix 47 m_cols(m_rank==dec.cols() ? 1 : dec.cols() - m_rank) 50 inline Index rows() const { return m_dec.cols(); } 51 inline Index cols() const { return m_cols; } function in struct:Eigen::internal::kernel_retval_base 76 using Base::cols; \
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/external/ceres-solver/internal/ceres/ |
H A D | 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()[matri [all...] |
H A D | 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()[ [all...] |
H A D | compressed_row_sparse_matrix_test.cc | 224 EXPECT_EQ(crsm->num_nonzeros(), crs_matrix.cols.size()); 232 EXPECT_EQ(crsm->cols()[i], crs_matrix.cols[i]); 284 int* cols = matrix_->mutable_cols(); local 288 cols[0] = 0; 292 cols[1] = 1; 296 cols[2] = 1; 298 cols[3] = 2; 302 cols[4] = 0; 304 cols[ 351 int* cols = matrix.mutable_cols(); local 438 vector<int> cols; local [all...] |
H A D | block_sparse_matrix.cc | 57 for (int i = 0; i < block_structure_->cols.size(); ++i) { 58 num_cols_ += block_structure_->cols[i].size; 70 int col_block_size = block_structure_->cols[col_block_id].size; 98 int col_block_size = block_structure_->cols[col_block_id].size; 99 int col_block_pos = block_structure_->cols[col_block_id].position; 118 int col_block_size = block_structure_->cols[col_block_id].size; 119 int col_block_pos = block_structure_->cols[col_block_id].position; 136 int col_block_size = block_structure_->cols[col_block_id].size; 137 int col_block_pos = block_structure_->cols[col_block_id].position; 153 int col_block_size = block_structure_->cols[col_block_i [all...] |
/external/eigen/Eigen/src/QR/ |
H A D | FullPivHouseholderQR.h | 94 FullPivHouseholderQR(Index rows, Index cols) argument 95 : m_qr(rows, cols), 96 m_hCoeffs((std::min)(rows,cols)), 97 m_rows_transpositions((std::min)(rows,cols)), 98 m_cols_transpositions((std::min)(rows,cols)), 99 m_cols_permutation(cols), 100 m_temp(cols), 110 * FullPivHouseholderQR<MatrixType> qr(matrix.rows(), matrix.cols()); 117 : m_qr(matrix.rows(), matrix.cols()), 118 m_hCoeffs((std::min)(matrix.rows(), matrix.cols())), 293 inline Index cols() const { return m_qr.cols(); } function in class:Eigen::FullPivHouseholderQR 412 Index cols = matrix.cols(); local 498 const Index rows = dec().rows(), cols = dec().cols(); local 571 const Index cols = m_qr.cols(); local 584 Index cols() const { return m_qr.rows(); } function in struct:Eigen::internal::FullPivHouseholderQRMatrixQReturnType [all...] |
H A D | 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]--;\
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/external/eigen/Eigen/src/Core/products/ |
H A D | 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)); \
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/external/eigen/Eigen/src/SVD/ |
H A D | 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 [all...] |
H A D | JacobiSVD.h | 79 if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols()) 82 ::new (&m_qr) QRType(svd.rows(), svd.cols()); 89 if(matrix.rows() > matrix.cols()) 92 svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>(); 124 if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols()) 127 ::new (&m_qr) QRType(svd.cols(), svd.rows()); 129 m_adjoint.resize(svd.cols(), sv 551 JacobiSVD(Index rows, Index cols, unsigned int computationOptions = 0) argument 741 inline Index cols() const { return m_cols; } function in class:Eigen::JacobiSVD 768 allocate(Index rows, Index cols, unsigned int computationOptions) argument [all...] |
/external/eigen/bench/ |
H A D | sparse_cholesky.cpp | 44 void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix& dst) argument 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; [all...] |
H A D | 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);
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/external/chromium_org/third_party/libvpx/source/libvpx/vp9/encoder/arm/neon/ |
H A D | vp9_subtract_neon.c | 17 void vp9_subtract_block_neon(int rows, int cols, argument 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)
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/external/chromium_org/third_party/pexpect/ |
H A D | screen.py | 69 self.cols = c 76 self.w = [ [SPACE] * self.cols for c in range(self.rows)] 98 top_bot = '+' + '-'*self.cols + '+\n' 103 self.fill_region (1,1,self.rows,self.cols, ch) 109 cs = constrain (cs, 1, self.cols) 110 ce = constrain (ce, 1, self.cols) 158 c = constrain (c, 1, self.cols) 177 c = constrain (c, 1, self.cols) 178 for ci in range (self.cols, c, -1): 189 c = constrain (c, 1, self.cols) [all...] |