&foo[0] -> foo.data() Use the more modern form of accessing the data array of a vector rather than grabbing the pointer to the first element. The latter can lead to errors if the vector is of zero length. Change-Id: Ifc8fc969b06b3ba1a9385e8a3a8d5c50b25db5a8
diff --git a/internal/ceres/accelerate_sparse.cc b/internal/ceres/accelerate_sparse.cc index b01414d..4331c29 100644 --- a/internal/ceres/accelerate_sparse.cc +++ b/internal/ceres/accelerate_sparse.cc
@@ -114,12 +114,12 @@ // Accelerate's columnStarts is a long*, not an int*. These types might be // different (e.g. ARM on iOS) so always make a copy. column_starts_.resize(A->num_rows() + 1); // +1 for final column length. - std::copy_n(A->rows(), column_starts_.size(), &column_starts_[0]); + std::copy_n(A->rows(), column_starts_.size(), column_starts_.data()); ASSparseMatrix At; At.structure.rowCount = A->num_cols(); At.structure.columnCount = A->num_rows(); - At.structure.columnStarts = &column_starts_[0]; + At.structure.columnStarts = column_starts_.data(); At.structure.rowIndices = A->mutable_cols(); At.structure.attributes.transpose = false; At.structure.attributes.triangle = SparseUpperTriangle;
diff --git a/internal/ceres/block_jacobian_writer.cc b/internal/ceres/block_jacobian_writer.cc index 727d649..d7e1e95 100644 --- a/internal/ceres/block_jacobian_writer.cc +++ b/internal/ceres/block_jacobian_writer.cc
@@ -94,7 +94,7 @@ jacobian_layout_storage->resize(num_jacobian_blocks); int e_block_pos = 0; - int* jacobian_pos = &(*jacobian_layout_storage)[0]; + int* jacobian_pos = jacobian_layout_storage->data(); for (int i = 0; i < residual_blocks.size(); ++i) { const ResidualBlock* residual_block = residual_blocks[i]; const int num_residuals = residual_block->NumResiduals(); @@ -144,7 +144,8 @@ auto preparers = std::make_unique<BlockEvaluatePreparer[]>(num_threads); for (unsigned i = 0; i < num_threads; i++) { - preparers[i].Init(&jacobian_layout_[0], max_derivatives_per_residual_block); + preparers[i].Init(jacobian_layout_.data(), + max_derivatives_per_residual_block); } return preparers; }
diff --git a/internal/ceres/compressed_row_sparse_matrix.h b/internal/ceres/compressed_row_sparse_matrix.h index d164bef..d98f61f 100644 --- a/internal/ceres/compressed_row_sparse_matrix.h +++ b/internal/ceres/compressed_row_sparse_matrix.h
@@ -110,8 +110,8 @@ int num_rows() const final { return num_rows_; } int num_cols() const final { return num_cols_; } int num_nonzeros() const final { return rows_[num_rows_]; } - const double* values() const final { return &values_[0]; } - double* mutable_values() final { return &values_[0]; } + const double* values() const final { return values_.data(); } + double* mutable_values() final { return values_.data(); } // Delete the bottom delta_rows. // num_rows -= delta_rows @@ -133,11 +133,11 @@ void set_num_cols(const int num_cols) { num_cols_ = num_cols; } // Low level access methods that expose the structure of the matrix. - const int* cols() const { return &cols_[0]; } - int* mutable_cols() { return &cols_[0]; } + const int* cols() const { return cols_.data(); } + int* mutable_cols() { return cols_.data(); } - const int* rows() const { return &rows_[0]; } - int* mutable_rows() { return &rows_[0]; } + const int* rows() const { return rows_.data(); } + int* mutable_rows() { return rows_.data(); } StorageType storage_type() const { return storage_type_; } void set_storage_type(const StorageType storage_type) {
diff --git a/internal/ceres/covariance_impl.cc b/internal/ceres/covariance_impl.cc index d6ce69b..bc4e75f 100644 --- a/internal/ceres/covariance_impl.cc +++ b/internal/ceres/covariance_impl.cc
@@ -600,9 +600,9 @@ cholmod_jacobian.ncol = num_cols; cholmod_jacobian.nzmax = num_nonzeros; cholmod_jacobian.nz = nullptr; - cholmod_jacobian.p = reinterpret_cast<void*>(&transpose_rows[0]); - cholmod_jacobian.i = reinterpret_cast<void*>(&transpose_cols[0]); - cholmod_jacobian.x = reinterpret_cast<void*>(&transpose_values[0]); + cholmod_jacobian.p = reinterpret_cast<void*>(transpose_rows.data()); + cholmod_jacobian.i = reinterpret_cast<void*>(transpose_cols.data()); + cholmod_jacobian.x = reinterpret_cast<void*>(transpose_values.data()); cholmod_jacobian.z = nullptr; cholmod_jacobian.stype = 0; // Matrix is not symmetric. cholmod_jacobian.itype = CHOLMOD_LONG;
diff --git a/internal/ceres/inner_product_computer.cc b/internal/ceres/inner_product_computer.cc index a75cbe5..f2d5457 100644 --- a/internal/ceres/inner_product_computer.cc +++ b/internal/ceres/inner_product_computer.cc
@@ -255,7 +255,7 @@ int nnz = 0; // Process the first term. - const InnerProductComputer::ProductTerm* current = &product_terms[0]; + const InnerProductComputer::ProductTerm* current = product_terms.data(); FILL_CRSM_COL_BLOCK; // Process the rest of the terms.
diff --git a/internal/ceres/reorder_program.cc b/internal/ceres/reorder_program.cc index eb37dc3..912fe3d 100644 --- a/internal/ceres/reorder_program.cc +++ b/internal/ceres/reorder_program.cc
@@ -129,7 +129,7 @@ if (parameter_block_ordering.NumGroups() <= 1) { // The user did not supply a useful ordering so just go ahead // and use AMD. - ss.Ordering(block_jacobian_transpose, OrderingType::AMD, &ordering[0]); + ss.Ordering(block_jacobian_transpose, OrderingType::AMD, ordering); } else { // The user supplied an ordering, so use CAMD. vector<int> constraints; @@ -142,9 +142,9 @@ // Renumber the entries of constraints to be contiguous integers // as CAMD requires that the group ids be in the range [0, // parameter_blocks.size() - 1]. - MapValuesToContiguousRange(constraints.size(), &constraints[0]); + MapValuesToContiguousRange(constraints.size(), constraints.data()); ss.ConstrainedApproximateMinimumDegreeOrdering( - block_jacobian_transpose, &constraints[0], ordering); + block_jacobian_transpose, constraints.data(), ordering); } } else if (linear_solver_ordering_type == ceres::NESDIS) { // If nested dissection is chosen as an ordering algorithm, then @@ -152,7 +152,7 @@ CHECK(SuiteSparse::IsNestedDissectionAvailable()) << "Congratulations, you found a Ceres bug! " << "Please report this error to the developers."; - ss.Ordering(block_jacobian_transpose, OrderingType::NESDIS, &ordering[0]); + ss.Ordering(block_jacobian_transpose, OrderingType::NESDIS, ordering); } else { LOG(FATAL) << "Congratulations, you found a Ceres bug! " << "Please report this error to the developers."; @@ -344,7 +344,7 @@ // Renumber the entries of constraints to be contiguous integers as // CAMD requires that the group ids be in the range [0, // parameter_blocks.size() - 1]. - MapValuesToContiguousRange(constraints.size(), &constraints[0]); + MapValuesToContiguousRange(constraints.size(), constraints.data()); // Compute a block sparse presentation of J'. std::unique_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose( @@ -355,7 +355,7 @@ vector<int> ordering(parameter_blocks.size(), 0); ss.ConstrainedApproximateMinimumDegreeOrdering( - block_jacobian_transpose, &constraints[0], &ordering[0]); + block_jacobian_transpose, constraints.data(), ordering.data()); ss.Free(block_jacobian_transpose); const vector<ParameterBlock*> parameter_blocks_copy(parameter_blocks); @@ -551,7 +551,7 @@ *tsm_block_jacobian_transpose, parameter_blocks, parameter_block_ordering, - &ordering[0]); + ordering.data()); } else if (sparse_linear_algebra_library_type == ACCELERATE_SPARSE) { // Accelerate does not provide a function to perform reordering without // performing a full symbolic factorisation. As such, we have nothing @@ -565,7 +565,7 @@ OrderingForSparseNormalCholeskyUsingEigenSparse( linear_solver_ordering_type, *tsm_block_jacobian_transpose, - &ordering[0]); + ordering.data()); } // Apply ordering.
diff --git a/internal/ceres/suitesparse.cc b/internal/ceres/suitesparse.cc index 85fc5b2..3f091b9 100644 --- a/internal/ceres/suitesparse.cc +++ b/internal/ceres/suitesparse.cc
@@ -189,7 +189,7 @@ cc_.nmethods = 1; cc_.method[0].ordering = CHOLMOD_GIVEN; cholmod_factor* factor = - cholmod_analyze_p(A, const_cast<int*>(&ordering[0]), nullptr, 0, &cc_); + cholmod_analyze_p(A, const_cast<int*>(ordering.data()), nullptr, 0, &cc_); if (cc_.status != CHOLMOD_OK) { *message = @@ -236,8 +236,8 @@ block_matrix.nrow = num_row_blocks; block_matrix.ncol = num_col_blocks; block_matrix.nzmax = block_rows.size(); - block_matrix.p = reinterpret_cast<void*>(&block_cols[0]); - block_matrix.i = reinterpret_cast<void*>(&block_rows[0]); + block_matrix.p = reinterpret_cast<void*>(block_cols.data()); + block_matrix.i = reinterpret_cast<void*>(block_rows.data()); block_matrix.x = nullptr; block_matrix.stype = A->stype; block_matrix.itype = CHOLMOD_INT;