Addressing reviews. Post 3dsc.hpp

features/include/pcl/features/cvfh.h

@@ -147,8 +147,8 @@ namespace pcl
       inline void
       getCentroidClusters (std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > & centroids)
       {
-        for (const auto& centroid: centroids_dominant_orientations_)
-          centroids.push_back (centroid);
+        centroids.insert (centroids.cend (), centroids_dominant_orientations_.cbegin (),
+                          centroids_dominant_orientations_.cend ());
       }
 
       /** \brief Get the normal centroids used to compute different CVFH descriptors

features/include/pcl/features/impl/board.hpp

@@ -440,8 +440,9 @@ pcl::BOARDLocalReferenceFrameEstimation<PointInT, PointNT, PointOutT>::computePo
     {
         return 0;
     }
-    const auto result = std::find(array.begin (), array.end (), 0);
-    return std::distance(array.begin (), result);
+    const auto result = std::find_if(array.cbegin (), array.cend (),
+                                     [](const auto& x) -> bool { return x;});
+    return std::distance(array.cbegin (), result);
   };
   const auto first_no_border = find_first_no_border_pie(check_margin_array_);
 

features/include/pcl/features/impl/brisk_2d.hpp

@@ -107,9 +107,7 @@ pcl::BRISK2DEstimation<PointInT, PointOutT, KeypointT, IntensityT>::generateKern
   // get the total number of points
   const auto rings = radius_list.size ();
   assert (radius_list.size () != 0 && radius_list.size () == number_list.size ());
-  points_ = 0; // remember the total number of points
-  for (const auto number: number_list)
-    points_ += number;
+  points_ = std::accumulate (number_list.cbegin (), number_list.cend (), 0);
 
   // set up the patterns
   pattern_points_ = new BriskPatternPoint[points_*scales_*n_rot_];

features/include/pcl/features/impl/fpfh.hpp

@@ -161,13 +161,14 @@ pcl::FPFHEstimation<PointInT, PointNT, PointOutT>::weightPointSPFHSignature (
     sum_f3 = 100.0 / sum_f3;           // histogram values sum up to 100
 
   // Adjust final FPFH values
-  auto last = std::transform(fpfh_histogram.data (),
-          fpfh_histogram.data () + nr_bins_f1, fpfh_histogram.data (),
-          [&sum_f1](const auto& data) { return data * static_cast<float> (sum_f1); });
-  last = std::transform(last, last + nr_bins_f2, last,
-          [&sum_f2](const auto& data) { return data * static_cast<float> (sum_f2); });
-  std::transform(last, last + nr_bins_f3, last,
-          [&sum_f3](const auto& data) { return data * static_cast<float> (sum_f3); });
+  const auto denormalize_with = [](const auto& factor)
+    {
+      return [&factor](const auto& data) { return data * static_cast<float> (factor); };
+    };
+  auto last = std::transform(fpfh_histogram.data (), fpfh_histogram.data () + nr_bins_f1,
+                             fpfh_histogram.data (), denormalize_with (sum_f1));
+  last = std::transform(last, last + nr_bins_f2, last, denormalize_with (sum_f2));
+  std::transform(last, last + nr_bins_f3, last, denormalize_with (sum_f3));
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////

features/include/pcl/features/impl/rops_estimation.hpp

@@ -487,7 +487,7 @@ pcl::ROPSEstimation <PointInT, PointOutT>::getDistributionMatrix (const unsigned
     matrix (row, col) += 1.0f;
   }
 
-  matrix /= static_cast <float> (std::min<std::size_t> (1, cloud.points.size ()));
+  matrix /= std::max<std::float> (1, cloud.points.size ());
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////