Add ccache instructions to azure pipeline

Setting a high limit on cache size Per-run stats only Removed ccache from Mac, negative performance impact
PointCloudLibrary · Sep 30, 2019 · 3181dfe · 3181dfe
1 parent 922387d
commit 3181dfe
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Showing 2 changed files with 25 additions and 20 deletions.
diff --git a/.ci/azure-pipelines/build-ubuntu.yml b/.ci/azure-pipelines/build-ubuntu.yml
@@ -13,11 +13,21 @@ jobs:
     variables:
       BUILD_DIR: '$(Agent.BuildDirectory)/build'
       CMAKE_CXX_FLAGS: '-Wall -Wextra -Wabi -O2'
+      CCACHE_DIR: $(Pipeline.Workspace)/ccache
+      CCACHE_MAXSIZE: 15G
     steps:
+      - task: CacheBeta@0
+        inputs:
+          key: ccache | gcc | $(Agent.OS)
+          path: $(CCACHE_DIR)
+        displayName: ccache
+      - script: ccache -z
+        displayName: 'Zero ccache statistics'
       - script: |
           mkdir $BUILD_DIR && cd $BUILD_DIR
           cmake $(Build.SourcesDirectory) \
             -DCMAKE_CXX_FLAGS="$CMAKE_CXX_FLAGS" \
+            -DPCL_DISABLE_CCACHE=OFF \
             -DPCL_ONLY_CORE_POINT_TYPES=ON \
             -DBUILD_simulation=ON \
             -DBUILD_surface_on_nurbs=ON \
@@ -41,6 +51,8 @@ jobs:
           cmake --build . -- test_filters test_registration test_registration_api
           cmake --build . -- -j2
         displayName: 'Build Library'
+      - script: ccache -s
+        displayName: 'Display ccache statistics'
       - script: |
           cd $BUILD_DIR/test
           ctest -V -T Test

diff --git a/features/include/pcl/features/impl/rops_estimation.hpp b/features/include/pcl/features/impl/rops_estimation.hpp
@@ -144,7 +144,7 @@ pcl::ROPSEstimation <PointInT, PointOutT>::computeFeature (PointCloudOut &output
 
   //feature size = number_of_rotations * number_of_axis_to_rotate_around * number_of_projections * number_of_central_moments
   unsigned int feature_size = number_of_rotations_ * 3 * 3 * 5;
-  unsigned int number_of_points = static_cast <unsigned int> (indices_->size ());
+  const auto number_of_points = indices_->size ();
   output.points.resize (number_of_points, PointOutT ());
 
   for (unsigned int i_point = 0; i_point < number_of_points; i_point++)
@@ -382,10 +382,10 @@ pcl::ROPSEstimation <PointInT, PointOutT>::computeEigenVectors (const Eigen::Mat
 template <typename PointInT, typename PointOutT> void
 pcl::ROPSEstimation <PointInT, PointOutT>::transformCloud (const PointInT& point, const Eigen::Matrix3f& matrix, const std::vector <int>& local_points, PointCloudIn& transformed_cloud) const
 {
-  const unsigned int number_of_points = static_cast <unsigned int> (local_points.size ());
+  const auto number_of_points = local_points.size ();
   transformed_cloud.points.resize (number_of_points, PointInT ());
 
-  for (unsigned int i = 0; i < number_of_points; i++)
+  for (std::size_t i = 0; i < number_of_points; i++)
   {
     Eigen::Vector3f transformed_point (
       surface_->points[local_points[i]].x - point.x,
@@ -417,7 +417,7 @@ pcl::ROPSEstimation <PointInT, PointOutT>::rotateCloud (const PointInT& axis, co
                      (1 - cosine) * y * x + sine * z,    cosine + (1 - cosine) * y * y,      (1 - cosine) * y * z - sine * x,
                      (1 - cosine) * z * x - sine * y,    (1 - cosine) * z * y + sine * x,    cosine + (1 - cosine) * z * z;
 
-  const unsigned int number_of_points = static_cast <unsigned int> (cloud.points.size ());
+  const auto number_of_points = cloud.points.size ();
 
   rotated_cloud.header = cloud.header;
   rotated_cloud.width = number_of_points;
@@ -431,7 +431,7 @@ pcl::ROPSEstimation <PointInT, PointOutT>::rotateCloud (const PointInT& axis, co
   max (1) = -std::numeric_limits <float>::max ();
   max (2) = -std::numeric_limits <float>::max ();
 
-  for (unsigned int i_point = 0; i_point < number_of_points; i_point++)
+  for (std::size_t i_point = 0; i_point < number_of_points; i_point++)
   {
     Eigen::Vector3f point (
       cloud.points[i_point].x,
@@ -445,13 +445,11 @@ pcl::ROPSEstimation <PointInT, PointOutT>::rotateCloud (const PointInT& axis, co
     rotated_point.z = point (2);
     rotated_cloud.points[i_point] = rotated_point;
 
-    if (min (0) > rotated_point.x) min (0) = rotated_point.x;
-    if (min (1) > rotated_point.y) min (1) = rotated_point.y;
-    if (min (2) > rotated_point.z) min (2) = rotated_point.z;
-
-    if (max (0) < rotated_point.x) max (0) = rotated_point.x;
-    if (max (1) < rotated_point.y) max (1) = rotated_point.y;
-    if (max (2) < rotated_point.z) max (2) = rotated_point.z;
+    for (int i = 0; i < 3; ++i)
+    {
+      min(i) = std::min(min(i), point(i));
+      max(i) = std::max(max(i), point(i));
+    }
   }
 }
 
@@ -461,8 +459,6 @@ pcl::ROPSEstimation <PointInT, PointOutT>::getDistributionMatrix (const unsigned
 {
   matrix.setZero ();
 
-  const unsigned int number_of_points = static_cast <unsigned int> (cloud.points.size ());
-
   const unsigned int coord[3][2] = {
     {0, 1},
     {0, 2},
@@ -471,12 +467,9 @@ pcl::ROPSEstimation <PointInT, PointOutT>::getDistributionMatrix (const unsigned
   const float u_bin_length = (max (coord[projection][0]) - min (coord[projection][0])) / number_of_bins_;
   const float v_bin_length = (max (coord[projection][1]) - min (coord[projection][1])) / number_of_bins_;
 
-  for (unsigned int i_point = 0; i_point < number_of_points; i_point++)
+  for (const auto& pt: cloud.points)
   {
-    Eigen::Vector3f point (
-      cloud.points[i_point].x,
-      cloud.points[i_point].y,
-      cloud.points[i_point].z);
+    Eigen::Vector3f point (pt.x, pt.y, pt.z);
 
     const float u_length = point (coord[projection][0]) - min[coord[projection][0]];
     const float v_length = point (coord[projection][1]) - min[coord[projection][1]];
@@ -492,7 +485,7 @@ pcl::ROPSEstimation <PointInT, PointOutT>::getDistributionMatrix (const unsigned
     matrix (row, col) += 1.0f;
   }
 
-  matrix /= static_cast <float> (number_of_points);
+  matrix /= static_cast <float> (std::min(1, cloud.points.size ()));
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////