clang-format

rapidsai · Sep 26, 2023 · dcdb388 · dcdb388
1 parent 3bfdd0d
commit dcdb388
Show file tree

Hide file tree

Showing 5 changed files with 15 additions and 24 deletions.
diff --git a/cpp/include/cuspatial/detail/index/construction/phase_1.cuh b/cpp/include/cuspatial/detail/index/construction/phase_1.cuh
@@ -147,10 +147,9 @@ inline std::tuple<IndexT, IndexT, std::vector<IndexT>, std::vector<IndexT>> buil
 
   // iterator for the parent level's quad node keys
   auto parent_keys = thrust::make_transform_iterator(
-    keys_begin,
-    cuda::proclaim_return_type<uint32_t>(
-      [] __device__(uint32_t const child_key) { return (child_key >> 2); }
-    ));
+    keys_begin, cuda::proclaim_return_type<uint32_t>([] __device__(uint32_t const child_key) {
+      return (child_key >> 2);
+    }));
 
   // iterator for the current level's quad node point and child counts
   auto child_nodes = thrust::make_zip_iterator(quad_point_count_begin, quad_child_count_begin);

diff --git a/cpp/include/cuspatial/detail/join/quadtree_bbox_filtering.cuh b/cpp/include/cuspatial/detail/join/quadtree_bbox_filtering.cuh
@@ -90,18 +90,14 @@ join_quadtree_and_bounding_boxes(point_quadtree_ref quadtree,
                                bounding_boxes_first,
                                // The top-level node indices
                                detail::make_counting_transform_iterator(
-                                 0,
-                                 cuda::proclaim_return_type<int32_t>(
-                                   [=] __device__(auto i) { return i % num_top_level_leaves; }
-                                 )
-                               ),
+                                 0, cuda::proclaim_return_type<int32_t>([=] __device__(auto i) {
+                                   return i % num_top_level_leaves;
+                                 })),
                                // The top-level bbox indices
                                detail::make_counting_transform_iterator(
-                                 0,
-                                 cuda::proclaim_return_type<int32_t>(
-                                   [=] __device__(auto i) { return i / num_top_level_leaves; }
-                                 )
-                               ),
+                                 0, cuda::proclaim_return_type<int32_t>([=] __device__(auto i) {
+                                   return i / num_top_level_leaves;
+                                 })),
                                make_current_level_iter(),  // intermediate intersections or parent
                                                            // quadrants found during traversal
                                // found intersecting quadrant and bbox indices for output

diff --git a/cpp/include/cuspatial/detail/join/quadtree_point_to_nearest_linestring.cuh b/cpp/include/cuspatial/detail/join/quadtree_point_to_nearest_linestring.cuh
@@ -249,8 +249,7 @@ quadtree_point_to_nearest_linestring(LinestringIndexIterator linestring_indices_
   auto all_point_indices =
     thrust::make_transform_iterator(all_point_linestring_indices_and_distances,
                                     cuda::proclaim_return_type<uint32_t>(
-                                      [] __device__(auto const& x) { return thrust::get<0>(x); }
-                                    ));
+                                      [] __device__(auto const& x) { return thrust::get<0>(x); }));
 
   // Allocate vectors for the distances min reduction
   auto num_points = std::distance(point_indices_first, point_indices_last);
@@ -291,8 +290,7 @@ quadtree_point_to_nearest_linestring(LinestringIndexIterator linestring_indices_
         }
         // Otherwise choose linestring with smallest distance
         return d_lhs < d_rhs ? lhs : rhs;
-      })
-    );
+      }));
 
   auto const num_distances = thrust::distance(point_idxs.begin(), point_idxs_end.first);
 

diff --git a/cpp/tests/distance/hausdorff_test.cu b/cpp/tests/distance/hausdorff_test.cu
@@ -152,10 +152,9 @@ void generic_hausdorff_test()
   auto zero_iter         = thrust::make_constant_iterator<vec_2d>({0, 0});
   auto counting_iter     = thrust::make_counting_iterator<uint32_t>(0);
   auto space_offset_iter = thrust::make_transform_iterator(
-    counting_iter,
-    cuda::proclaim_return_type<uint32_t>(
-      [] __device__(auto idx) { return idx * elements_per_space; }
-    ));
+    counting_iter, cuda::proclaim_return_type<uint32_t>([] __device__(auto idx) {
+      return idx * elements_per_space;
+    }));
 
   auto distances = rmm::device_vector<T>(num_distances);
   auto expected  = rmm::device_vector<T>(num_distances, 0);

diff --git a/cpp/tests/trajectory/trajectory_distances_and_speeds_test.cu b/cpp/tests/trajectory/trajectory_distances_and_speeds_test.cu
@@ -69,8 +69,7 @@ struct TrajectoryDistancesAndSpeedsTest : public ::testing::Test {
                      expected_speeds.end(),
                      std::numeric_limits<T>::lowest(),
                      cuda::proclaim_return_type<T>(
-                      [] __device__(T const& a, T const& b) { return max(abs(a), abs(b)); }
-      ));
+                       [] __device__(T const& a, T const& b) { return max(abs(a), abs(b)); }));
 
     // We expect the floating point error (in ulps) due to be proportional to the  number of
     // operations to compute the relevant quantity. For distance, this computation is