ClangTidy cleanups
Change-Id: I514ca5fd91c08866b412021e6c0f5d6f97c4bf8f
diff --git a/internal/ceres/iterative_schur_complement_solver.cc b/internal/ceres/iterative_schur_complement_solver.cc
index 0d0daaa..5f56be2 100644
--- a/internal/ceres/iterative_schur_complement_solver.cc
+++ b/internal/ceres/iterative_schur_complement_solver.cc
@@ -95,7 +95,7 @@
reduced_linear_system_solution_.setZero();
CreatePreconditioner(A);
- if (preconditioner_.get() != nullptr) {
+ if (preconditioner_ != nullptr) {
if (!preconditioner_->Update(*A, per_solve_options.D)) {
LinearSolver::Summary summary;
summary.num_iterations = 0;
@@ -141,7 +141,7 @@
void IterativeSchurComplementSolver::CreatePreconditioner(
BlockSparseMatrix* A) {
- if (preconditioner_.get() != nullptr) {
+ if (preconditioner_ != nullptr) {
return;
}
diff --git a/internal/ceres/linear_least_squares_problems.cc b/internal/ceres/linear_least_squares_problems.cc
index b8633aa..6cee2f6 100644
--- a/internal/ceres/linear_least_squares_problems.cc
+++ b/internal/ceres/linear_least_squares_problems.cc
@@ -88,8 +88,7 @@
2.82327586;]
*/
std::unique_ptr<LinearLeastSquaresProblem> LinearLeastSquaresProblem0() {
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
auto A = std::make_unique<TripletSparseMatrix>(3, 2, 6);
problem->b = std::make_unique<double[]>(3);
@@ -190,8 +189,8 @@
int num_rows = 6;
int num_cols = 5;
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
+
auto A = std::make_unique<TripletSparseMatrix>(
num_rows, num_cols, num_rows * num_cols);
problem->b = std::make_unique<double[]>(num_rows);
@@ -302,8 +301,7 @@
int num_rows = 6;
int num_cols = 5;
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
problem->b = std::make_unique<double[]>(num_rows);
problem->D = std::make_unique<double[]>(num_cols);
@@ -317,8 +315,7 @@
problem->x[4] = 0.1388;
auto* bs = new CompressedRowBlockStructure;
- std::unique_ptr<double[]> values =
- std::make_unique<double[]>(num_rows * num_cols);
+ auto values = std::make_unique<double[]>(num_rows * num_cols);
for (int c = 0; c < num_cols; ++c) {
bs->cols.emplace_back();
@@ -444,16 +441,14 @@
int num_rows = 5;
int num_cols = 2;
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
problem->b = std::make_unique<double[]>(num_rows);
problem->D = std::make_unique<double[]>(num_cols);
problem->num_eliminate_blocks = 2;
auto* bs = new CompressedRowBlockStructure;
- std::unique_ptr<double[]> values =
- std::make_unique<double[]>(num_rows * num_cols);
+ auto values = std::make_unique<double[]>(num_rows * num_cols);
for (int c = 0; c < num_cols; ++c) {
bs->cols.emplace_back();
@@ -553,16 +548,14 @@
int num_rows = 3;
int num_cols = 7;
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
problem->b = std::make_unique<double[]>(num_rows);
problem->D = std::make_unique<double[]>(num_cols);
problem->num_eliminate_blocks = 1;
auto* bs = new CompressedRowBlockStructure;
- std::unique_ptr<double[]> values =
- std::make_unique<double[]>(num_rows * num_cols);
+ auto values = std::make_unique<double[]>(num_rows * num_cols);
// Column block structure
bs->cols.emplace_back();
@@ -685,9 +678,7 @@
int num_rows = 6;
int num_cols = 5;
- std::unique_ptr<LinearLeastSquaresProblem> problem =
- std::make_unique<LinearLeastSquaresProblem>();
-
+ auto problem = std::make_unique<LinearLeastSquaresProblem>();
problem->b = std::make_unique<double[]>(num_rows);
problem->D = std::make_unique<double[]>(num_cols);
problem->num_eliminate_blocks = 2;
@@ -701,8 +692,7 @@
problem->x[4] = 0.1;
auto* bs = new CompressedRowBlockStructure;
- std::unique_ptr<double[]> values =
- std::make_unique<double[]>(num_rows * num_cols);
+ auto values = std::make_unique<double[]>(num_rows * num_cols);
for (int c = 0; c < num_cols; ++c) {
bs->cols.emplace_back();
diff --git a/internal/ceres/schur_complement_solver.cc b/internal/ceres/schur_complement_solver.cc
index 1f10ac2..5c81c33 100644
--- a/internal/ceres/schur_complement_solver.cc
+++ b/internal/ceres/schur_complement_solver.cc
@@ -114,7 +114,7 @@
EventLogger event_logger("SchurComplementSolver::Solve");
const CompressedRowBlockStructure* bs = A->block_structure();
- if (eliminator_.get() == nullptr) {
+ if (eliminator_ == nullptr) {
const int num_eliminate_blocks = options_.elimination_groups[0];
const int num_f_blocks = bs->cols.size() - num_eliminate_blocks;
@@ -354,7 +354,7 @@
// Only SCHUR_JACOBI is supported over here right now.
CHECK_EQ(options().preconditioner_type, SCHUR_JACOBI);
- if (preconditioner_.get() == nullptr) {
+ if (preconditioner_ == nullptr) {
preconditioner_ =
std::make_unique<BlockRandomAccessDiagonalMatrix>(blocks_);
}
diff --git a/internal/ceres/solver_test.cc b/internal/ceres/solver_test.cc
index 3f9f8a1..b4b2d34 100644
--- a/internal/ceres/solver_test.cc
+++ b/internal/ceres/solver_test.cc
@@ -33,6 +33,7 @@
#include <cmath>
#include <limits>
#include <memory>
+#include <string>
#include <vector>
#include "ceres/autodiff_cost_function.h"
