ClangTidy cleanups

Change-Id: I514ca5fd91c08866b412021e6c0f5d6f97c4bf8f

internal/ceres/iterative_schur_complement_solver.cc

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;
   }
 

internal/ceres/linear_least_squares_problems.cc

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();

internal/ceres/schur_complement_solver.cc

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_);
   }

internal/ceres/solver_test.cc

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"