style(pre-commit): autofix

Author: pre-commit-ci[bot]

localization/autoware_localization_util/test/test_tpe.cpp

@@ -89,7 +89,7 @@ TEST(TreeStructuredParzenEstimatorTest, MinimizationTest)
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MINIMIZE, k_trials_num / 2, sample_mean,
     sample_stddev);
-  
+
   for (int64_t trial = 0; trial < k_trials_num; trial++) {
     const TreeStructuredParzenEstimator::Input input = estimator.get_next_input();
     const double score = quadratic_function(input);
@@ -114,7 +114,7 @@ TEST(TreeStructuredParzenEstimatorTest, SingleDimensionTest)
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MAXIMIZE, k_trials_num / 2, sample_mean,
     sample_stddev);
-  
+
   for (int64_t trial = 0; trial < k_trials_num; trial++) {
     const TreeStructuredParzenEstimator::Input input = estimator.get_next_input();
     const double score = linear_function(input);
@@ -132,7 +132,7 @@ TEST(TreeStructuredParzenEstimatorTest, EmptyTrials)
 
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MAXIMIZE, 10, sample_mean, sample_stddev);
-  
+
   // Should not crash when getting input without any trials
   const TreeStructuredParzenEstimator::Input input = estimator.get_next_input();
   EXPECT_EQ(input.size(), 2u);
@@ -145,11 +145,11 @@ TEST(TreeStructuredParzenEstimatorTest, SingleTrial)
 
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MAXIMIZE, 0, sample_mean, sample_stddev);
-  
+
   // Add one trial
   const TreeStructuredParzenEstimator::Input first_input{1.0, 1.0};
   estimator.add_trial({first_input, 1.0});
-  
+
   // Should be able to get next input
   const TreeStructuredParzenEstimator::Input next_input = estimator.get_next_input();
   EXPECT_EQ(next_input.size(), 2u);
@@ -160,10 +160,10 @@ TEST(TreeStructuredParzenEstimatorTest, LogGaussianPdf)
   TreeStructuredParzenEstimator::Input input{1.0, 2.0};
   TreeStructuredParzenEstimator::Input mu{1.0, 2.0};
   TreeStructuredParzenEstimator::Input sigma{1.0, 1.0};
-  
+
   double log_pdf = TreeStructuredParzenEstimator::log_gaussian_pdf(input, mu, sigma);
   EXPECT_NEAR(log_pdf, -1.8378770664093453, 1e-6);  // Expected value calculated manually
-  
+
   // Test with different sigma
   TreeStructuredParzenEstimator::Input sigma2{0.5, 0.5};
   log_pdf = TreeStructuredParzenEstimator::log_gaussian_pdf(input, mu, sigma2);
@@ -177,18 +177,18 @@ TEST(TreeStructuredParzenEstimatorTest, DifferentSampleStddev)
 
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MAXIMIZE, 10, sample_mean, sample_stddev);
-  
+
   // Add some trials
   for (int i = 0; i < 5; ++i) {
     TreeStructuredParzenEstimator::Input input{0.1 * i, 0.01 * i, 1.0 * i};
     estimator.add_trial({input, static_cast<double>(i)});
   }
-  
+
   // Get next input and verify it's within reasonable bounds
   const TreeStructuredParzenEstimator::Input next_input = estimator.get_next_input();
-  EXPECT_NEAR(next_input[0], 0.0, 2.0);  // stddev = 1.0
-  EXPECT_NEAR(next_input[1], 0.0, 0.2);  // stddev = 0.1
-  EXPECT_NEAR(next_input[2], 0.0, 20.0); // stddev = 10.0
+  EXPECT_NEAR(next_input[0], 0.0, 2.0);   // stddev = 1.0
+  EXPECT_NEAR(next_input[1], 0.0, 0.2);   // stddev = 0.1
+  EXPECT_NEAR(next_input[2], 0.0, 20.0);  // stddev = 10.0
 }
 
 TEST(TreeStructuredParzenEstimatorTest, ComputeLogLikelihoodRatio)
@@ -198,17 +198,17 @@ TEST(TreeStructuredParzenEstimatorTest, ComputeLogLikelihoodRatio)
 
   TreeStructuredParzenEstimator estimator(
     TreeStructuredParzenEstimator::Direction::MAXIMIZE, 0, sample_mean, sample_stddev);
-  
+
   // Add some trials
   for (int i = 0; i < 10; ++i) {
     TreeStructuredParzenEstimator::Input input{0.1 * i, 0.1 * i};
     estimator.add_trial({input, static_cast<double>(i)});
   }
-  
+
   // Test likelihood ratio for a point
   TreeStructuredParzenEstimator::Input test_point{0.5, 0.5};
   double ratio = estimator.compute_log_likelihood_ratio(test_point);
-  
+
   // The exact value depends on the random sampling, but we can check it's finite
   EXPECT_TRUE(std::isfinite(ratio));
 }