Prefer usage of operator/= instead of using operator/

gpu/people/src/probability_processor.cpp

@@ -111,7 +111,7 @@ pcl::gpu::people::ProbabilityProcessor::CreateGaussianKernel ( float sigma,
   // Normalize f
   for(int i = 0; i < kernelSize; i++)
   {
-    f[i] = f[i]/sum;
+    f[i] /=sum;
   }
 
   return f;

ml/src/svm.cpp

@@ -2095,7 +2095,7 @@ static void sigmoid_train (
         break;
       }
       else
-        stepsize = stepsize / 2.0;
+        stepsize /= 2.0;
     }
 
     if (stepsize < min_step)

ml/src/svm_wrapper.cpp

@@ -869,7 +869,7 @@ pcl::SVMClassify::scaleProblem (svm_problem &input, svm_scaling scaling)
         break;
 
       if (input.x[i][j].index < scaling.max && scaling.obj[ input.x[i][j].index ].index == 1)
-        input.x[i][j].value = input.x[i][j].value / scaling.obj[ input.x[i][j].index ].value;
+        input.x[i][j].value /= scaling.obj[ input.x[i][j].index ].value;
 
       j++;
     }

recognition/src/face_detection/rf_face_detector_trainer.cpp

@@ -163,7 +163,7 @@ void pcl::RFFaceDetectorTrainer::faceVotesClustering()
         }
       }
 
-      mean = mean / static_cast<float> (good_votes);
+      mean /= static_cast<float> (good_votes);
       clusters_mean[i] = mean;
     }
 
@@ -202,14 +202,14 @@ void pcl::RFFaceDetectorTrainer::faceVotesClustering()
         rot += angle_votes_[uncertainty[j].first];
       }
 
-      rot = rot / static_cast<float> (num);
+      rot /= static_cast<float> (num);
 
       Eigen::Vector3f pos;
       pos.setZero ();
       for (int j = 0; j < num; j++)
         pos += head_center_votes_[uncertainty[j].first];
 
-      pos = pos / static_cast<float> (num);
+      pos /= static_cast<float> (num);
 
       head_clusters_centers_.push_back (pos); //clusters_mean[i]
       head_clusters_rotation_.push_back (rot);

registration/src/gicp6d.cpp

@@ -58,17 +58,17 @@ namespace pcl
     if (R > 0.04045)
       R = pow ( (R + 0.055) / 1.055, 2.4);
     else
-      R = R / 12.92;
+      R /= 12.92;
 
     if (G > 0.04045)
       G = pow ( (G + 0.055) / 1.055, 2.4);
     else
-      G = G / 12.92;
+      G /= 12.92;
 
     if (B > 0.04045)
       B = pow ( (B + 0.055) / 1.055, 2.4);
     else
-      B = B / 12.92;
+      B /= 12.92;
 
     // postponed:
     //    R *= 100.0;

simulation/src/range_likelihood.cpp

@@ -109,8 +109,8 @@ max_level (int a, int b)
   while (true)
   {
     if (a%2 || b%2) return level;
-    a = a / 2;
-    b = b / 2;
+    a /= 2;
+    b /= 2;
     level++;
   }
 }

simulation/src/sum_reduce.cpp

@@ -37,8 +37,8 @@ pcl::simulation::SumReduce::SumReduce (int width, int height, int levels) : leve
 
   for (int i = 0; i < levels_; ++i)
   {
-    level_width = level_width / 2;
-    level_height = level_height / 2;
+    level_width /= 2;
+    level_height /= 2;
 
     glBindTexture (GL_TEXTURE_2D, arrays_[i]);
     glTexParameteri (GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE);
@@ -105,8 +105,8 @@ pcl::simulation::SumReduce::sum (GLuint input_array, float* output_array)
       std::cout << "SumReduce::sum  render" << std::endl;
     }
 
-    width = width / 2;
-    height = height / 2;
+    width /= 2;
+    height /= 2;
 
     glActiveTexture (GL_TEXTURE0);
     glBindTexture (GL_TEXTURE_2D, arrays_[i]);

surface/include/pcl/surface/impl/texture_mapping.hpp

@@ -55,19 +55,19 @@ pcl::TextureMapping<PointInT>::mapTexture2Face (
   Eigen::Vector3f p2p3 (p3[0] - p2[0], p3[1] - p2[1], p3[2] - p2[2]);
 
   // Normalize
-  p1p2 = p1p2 / std::sqrt (p1p2.dot (p1p2));
-  p1p3 = p1p3 / std::sqrt (p1p3.dot (p1p3));
-  p2p3 = p2p3 / std::sqrt (p2p3.dot (p2p3));
+  p1p2 /= std::sqrt (p1p2.dot (p1p2));
+  p1p3 /= std::sqrt (p1p3.dot (p1p3));
+  p2p3 /= std::sqrt (p2p3.dot (p2p3));
 
   // compute vector normal of a face
   Eigen::Vector3f f_normal = p1p2.cross (p1p3);
-  f_normal = f_normal / std::sqrt (f_normal.dot (f_normal));
+  f_normal /= std::sqrt (f_normal.dot (f_normal));
 
   // project vector field onto the face: vector v1_projected = v1 - Dot(v1, n) * n;
   Eigen::Vector3f f_vector_field = vector_field_ - vector_field_.dot (f_normal) * f_normal;
 
   // Normalize
-  f_vector_field = f_vector_field / std::sqrt (f_vector_field.dot (f_vector_field));
+  f_vector_field /= std::sqrt (f_vector_field.dot (f_vector_field));
 
   // texture coordinates
   Eigen::Vector2f tp1, tp2, tp3;

surface/include/pcl/surface/texture_mapping.h

@@ -142,7 +142,7 @@ namespace pcl
       {
         vector_field_ = Eigen::Vector3f (x, y, z);
         // normalize vector field
-        vector_field_ = vector_field_ / std::sqrt (vector_field_.dot (vector_field_));
+        vector_field_ /= std::sqrt (vector_field_.dot (vector_field_));
       }
 
       /** \brief Set texture files

surface/src/on_nurbs/fitting_curve_2d.cpp

@@ -296,7 +296,7 @@ FittingCurve2d::initNurbsPCA (int order, NurbsDataCurve2d *data, int ncps)
   data->mean = mean;
   data->eigenvectors = eigenvectors;
 
-  eigenvalues = eigenvalues / s; // seems that the eigenvalues are dependent on the number of points (???)
+  eigenvalues /= s; // seems that the eigenvalues are dependent on the number of points (???)
   Eigen::Matrix2d eigenvectors_inv = eigenvectors.inverse ();
 
   Eigen::Vector2d v_max (-DBL_MAX, -DBL_MAX);

surface/src/on_nurbs/fitting_curve_pdm.cpp

@@ -255,7 +255,7 @@ FittingCurve::initNurbsCurvePCA (int order, const vector_vec3d &data, int ncps,
 
   NurbsTools::pca (data, mean, eigenvectors, eigenvalues);
 
-  eigenvalues = eigenvalues / s; // seems that the eigenvalues are dependent on the number of points (???)
+  eigenvalues /= s; // seems that the eigenvalues are dependent on the number of points (???)
 
   double r = rf * sqrt (eigenvalues (0));
 

surface/src/on_nurbs/fitting_cylinder_pdm.cpp

@@ -227,7 +227,7 @@ FittingCylinder::initNurbsPCACylinder (int order, NurbsDataSurface *data)
   data->mean = mean;
   data->eigenvectors = eigenvectors;
 
-  eigenvalues = eigenvalues / s; // seems that the eigenvalues are dependent on the number of points (???)
+  eigenvalues /= s; // seems that the eigenvalues are dependent on the number of points (???)
 
   Eigen::Vector3d v_max (0.0, 0.0, 0.0);
   Eigen::Vector3d v_min (DBL_MAX, DBL_MAX, DBL_MAX);

surface/src/on_nurbs/fitting_surface_pdm.cpp

@@ -412,7 +412,7 @@ FittingSurface::initNurbsPCA (int order, NurbsDataSurface *m_data, Eigen::Vector
   if (eigenvectors.col (2).dot (z) < 0.0)
     flip = true;
 
-  eigenvalues = eigenvalues / s; // seems that the eigenvalues are dependent on the number of points (???)
+  eigenvalues /= s; // seems that the eigenvalues are dependent on the number of points (???)
 
   Eigen::Vector3d sigma (sqrt (eigenvalues (0)), sqrt (eigenvalues (1)), sqrt (eigenvalues (2)));
 
@@ -461,7 +461,7 @@ FittingSurface::initNurbsPCABoundingBox (int order, NurbsDataSurface *m_data, Ei
   if (eigenvectors.col (2).dot (z) < 0.0)
     flip = true;
 
-  eigenvalues = eigenvalues / s; // seems that the eigenvalues are dependent on the number of points (???)
+  eigenvalues /= s; // seems that the eigenvalues are dependent on the number of points (???)
   Eigen::Matrix3d eigenvectors_inv = eigenvectors.inverse ();
 
   Eigen::Vector3d v_max (-DBL_MAX, -DBL_MAX, -DBL_MAX);

tools/obj_rec_ransac_accepted_hypotheses.cpp

@@ -359,9 +359,9 @@ update (CallbackParameters* params)
   axis(2,0) = static_cast<float> (aux::getRandomInteger (-100, 100));
   // Normalize the axis
   float len = std::sqrt (axis(0,0)*axis(0,0) + axis(1,0)*axis(1,0) + axis(2,0)*axis(2,0));
-  axis(0,0) = axis(0,0)/len;
-  axis(1,0) = axis(1,0)/len;
-  axis(2,0) = axis(2,0)/len;
+  axis(0,0) /=len;
+  axis(1,0) /=len;
+  axis(2,0) /=len;
 
   cout << "Input angle = " << angle << endl;
   cout << "Input axis = \n" << axis << endl;

tracking/include/pcl/tracking/impl/particle_filter.hpp

@@ -154,7 +154,7 @@ pcl::tracking::ParticleFilterTracker<PointInT, StateT>::normalizeWeight ()
     if (sum != 0.0)
     {
       for ( size_t i = 0; i < particles_->points.size (); i++ )
-        particles_->points[i].weight =  particles_->points[i].weight / static_cast<float> (sum);
+        particles_->points[i].weight /= static_cast<float> (sum);
     }
     else
     {

visualization/include/pcl/visualization/common/impl/common.hpp

@@ -70,7 +70,7 @@ namespace pcl
     {
       Eigen::Vector4d pte (pt.x, pt.y, pt.z, 1);
       window_cord = composite_mat * pte;
-      window_cord = window_cord/window_cord (3);
+      window_cord /=window_cord (3);
       window_cord[0] = (window_cord[0]+1.0) / 2.0*window_size[0];
       window_cord[1] = (window_cord[1]+1.0) / 2.0*window_size[1];
       window_cord[2] = (window_cord[2]+1.0) / 2.0;