Fix MSVC warning C26814: "The const variable 'variable' can be computed at compile time. Consider using constexpr.."

Author: SunBlack

apps/in_hand_scanner/src/icp.cpp

@@ -161,7 +161,7 @@ pcl::ihs::ICP::findTransformation(const MeshConstPtr& mesh_model,
 {
   // Check the input
   // TODO: Double check the minimum number of points necessary for icp
-  const std::size_t n_min = 4;
+  constexpr std::size_t n_min = 4;
 
   if (mesh_model->sizeVertices() < n_min || cloud_data->size() < n_min) {
     std::cerr << "ERROR in icp.cpp: Not enough input points!\n";

apps/in_hand_scanner/src/main_window.cpp

@@ -70,7 +70,7 @@ pcl::ihs::MainWindow::MainWindow(QWidget* parent)
   spacer->setSizePolicy(QSizePolicy::Expanding, QSizePolicy::Expanding);
   ui_->toolBar->insertWidget(ui_->actionHelp, spacer);
 
-  const double max = std::numeric_limits<double>::max();
+  constexpr double max = std::numeric_limits<double>::max();
 
   // In hand scanner
   QHBoxLayout* layout = new QHBoxLayout(ui_->placeholder_in_hand_scanner);

apps/in_hand_scanner/src/opengl_viewer.cpp

@@ -484,7 +484,7 @@ pcl::ihs::OpenGLViewer::addMesh(const CloudXYZRGBNormalConstPtr& cloud,
   const int h = cloud->height;
   const int offset_1 = -w;
   const int offset_2 = -w - 1;
-  const int offset_3 = -1;
+  constexpr int offset_3 = -1;
 
   FaceVertexMeshPtr mesh(new FaceVertexMesh());
   mesh->transformation = T;
@@ -1083,7 +1083,7 @@ pcl::ihs::OpenGLViewer::initializeGL()
 void
 pcl::ihs::OpenGLViewer::setupViewport(const int w, const int h)
 {
-  const float aspect_ratio = 4. / 3.;
+  constexpr float aspect_ratio = 4. / 3.;
 
   // Use the biggest possible area of the window to draw to
   //    case 1 (w < w_scaled):        case 2 (w >= w_scaled):

apps/src/openni_mobile_server.cpp

@@ -79,7 +79,7 @@ CopyPointCloudToBuffers(const pcl::PointCloud<pcl::PointXYZRGBA>::ConstPtr& clou
         point.x > bounds_max.x || point.y > bounds_max.y || point.z > bounds_max.z)
       continue;
 
-    const int conversion_factor = 500;
+    constexpr int conversion_factor = 500;
 
     cloud_buffers.points[j * 3 + 0] = static_cast<short>(point.x * conversion_factor);
     cloud_buffers.points[j * 3 + 1] = static_cast<short>(point.y * conversion_factor);

apps/src/pyramid_surface_matching.cpp

@@ -9,7 +9,7 @@ using namespace pcl;
 #include <iostream>
 
 const Eigen::Vector4f subsampling_leaf_size(0.02f, 0.02f, 0.02f, 0.0f);
-const float normal_estimation_search_radius = 0.05f;
+constexpr float normal_estimation_search_radius = 0.05f;
 
 void
 subsampleAndCalculateNormals(PointCloud<PointXYZ>::Ptr& cloud,

common/include/pcl/common/impl/eigen.hpp

@@ -89,7 +89,7 @@ computeRoots (const Matrix& m, Roots& roots)
     computeRoots2 (c2, c1, roots);
   else
   {
-    const Scalar s_inv3 = Scalar (1.0 / 3.0);
+    constexpr Scalar s_inv3 = Scalar(1.0 / 3.0);
     const Scalar s_sqrt3 = std::sqrt (Scalar (3.0));
     // Construct the parameters used in classifying the roots of the equation
     // and in solving the equation for the roots in closed form.

common/include/pcl/point_representation.h

@@ -250,7 +250,7 @@ namespace pcl
       template<typename Key> inline void operator() ()
       {
         using FieldT = typename pcl::traits::datatype<PointDefault, Key>::type;
-        const int NrDims = pcl::traits::datatype<PointDefault, Key>::size;
+        constexpr int NrDims = pcl::traits::datatype<PointDefault, Key>::size;
         Helper<Key, FieldT, NrDims>::copyPoint (p1_, p2_, f_idx_);
       }
 

common/include/pcl/register_point_struct.h

@@ -100,7 +100,7 @@ namespace pcl
     plus (std::remove_const_t<T> &l, const T &r)
     {
       using type = std::remove_all_extents_t<T>;
-      static const std::uint32_t count = sizeof (T) / sizeof (type);
+      constexpr std::uint32_t count = sizeof(T) / sizeof(type);
       for (std::uint32_t i = 0; i < count; ++i)
         l[i] += r[i];
     }
@@ -117,7 +117,7 @@ namespace pcl
     plusscalar (T1 &p, const T2 &scalar)
     {
       using type = std::remove_all_extents_t<T1>;
-      static const std::uint32_t count = sizeof (T1) / sizeof (type);
+      constexpr std::uint32_t count = sizeof(T1) / sizeof(type);
       for (std::uint32_t i = 0; i < count; ++i)
         p[i] += scalar;
     }
@@ -134,7 +134,7 @@ namespace pcl
     minus (std::remove_const_t<T> &l, const T &r)
     {
       using type = std::remove_all_extents_t<T>;
-      static const std::uint32_t count = sizeof (T) / sizeof (type);
+      constexpr std::uint32_t count = sizeof(T) / sizeof(type);
       for (std::uint32_t i = 0; i < count; ++i)
         l[i] -= r[i];
     }
@@ -151,7 +151,7 @@ namespace pcl
     minusscalar (T1 &p, const T2 &scalar)
     {
       using type = std::remove_all_extents_t<T1>;
-      static const std::uint32_t count = sizeof (T1) / sizeof (type);
+      constexpr std::uint32_t count = sizeof(T1) / sizeof(type);
       for (std::uint32_t i = 0; i < count; ++i)
         p[i] -= scalar;
     }
@@ -168,7 +168,7 @@ namespace pcl
     mulscalar (T1 &p, const T2 &scalar)
     {
       using type = std::remove_all_extents_t<T1>;
-      static const std::uint32_t count = sizeof (T1) / sizeof (type);
+      constexpr std::uint32_t count = sizeof(T1) / sizeof(type);
       for (std::uint32_t i = 0; i < count; ++i)
         p[i] *= scalar;
     }
@@ -185,7 +185,7 @@ namespace pcl
     divscalar (T1 &p, const T2 &scalar)
     {
       using type = std::remove_all_extents_t<T1>;
-      static const std::uint32_t count = sizeof (T1) / sizeof (type);
+      constexpr std::uint32_t count = sizeof (T1) / sizeof (type);
       for (std::uint32_t i = 0; i < count; ++i)
         p[i] /= scalar;
     }
@@ -202,7 +202,7 @@ namespace pcl
     divscalar2 (ArrayT &p, const ScalarT &scalar)
     {
       using type = std::remove_all_extents_t<ArrayT>;
-      static const std::uint32_t count = sizeof (ArrayT) / sizeof (type);
+      constexpr std::uint32_t count = sizeof (ArrayT) / sizeof (type);
       for (std::uint32_t i = 0; i < count; ++i)
         p[i] = scalar / p[i];
     }

examples/features/example_difference_of_normals.cpp

@@ -99,7 +99,7 @@ int main (int argc, char *argv[])
 
     // Create downsampled point cloud for DoN NN search with large scale
     large_cloud_downsampled = PointCloud<PointT>::Ptr(new pcl::PointCloud<PointT>);
-    const float largedownsample = float (scale2/decimation);
+    constexpr float largedownsample = float(scale2 / decimation);
     sor.setLeafSize (largedownsample, largedownsample, largedownsample);
     sor.filter (*large_cloud_downsampled);
     std::cout << "Using leaf size of " << largedownsample << " for large scale, " << large_cloud_downsampled->size() << " points" << std::endl;

examples/keypoints/example_sift_z_keypoint_estimation.cpp

@@ -75,10 +75,10 @@ main(int, char** argv)
   std::cout << "points: " << cloud_xyz->size () <<std::endl;
 
   // Parameters for sift computation
-  const float min_scale = 0.005f;
-  const int n_octaves = 6;
-  const int n_scales_per_octave = 4;
-  const float min_contrast = 0.005f;
+  constexpr float min_scale = 0.005f;
+  constexpr int n_octaves = 6;
+  constexpr int n_scales_per_octave = 4;
+  constexpr float min_contrast = 0.005f;
 
   // Estimate the sift interest points using z values from xyz as the Intensity variants
   pcl::SIFTKeypoint<pcl::PointXYZ, pcl::PointWithScale> sift;