Rewrite unit test for NormalSpaceSampling

Author: SergioRAgostinho

filters/include/pcl/filters/impl/normal_space.hpp

@@ -155,14 +155,12 @@ pcl::NormalSpaceSampling<PointT, NormalT>::applyFilter (std::vector<int> &indice
 
       unsigned int pos = 0;
       unsigned int random_index = 0;
-      // std::uniform_int_distribution<unsigned> rng_uniform_distribution (0u, M - 1u); Test fails with this
-      std::uniform_int_distribution<unsigned> rng_uniform_distribution (0u, input_->size ());
+      std::uniform_int_distribution<unsigned> rng_uniform_distribution (0u, M - 1u);
 
       // Picking up a sample at random from jth bin
       do
       {
-        // random_index = rng_uniform_distribution (rng_); // Test fails with this combo
-        random_index = rng_uniform_distribution (rng_) % M;
+        random_index = rng_uniform_distribution (rng_);
         pos = start_index[j] + random_index;
       } while (is_sampled_flag.test (pos));
 

test/filters/test_sampling.cpp

@@ -105,31 +105,56 @@ TEST (CovarianceSampling, Filters)
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
 TEST (NormalSpaceSampling, Filters)
 {
+  // ensuring normals have unit norm
+  std::array<PointNormal, 16> points = {
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, -0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, -0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, -0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, -0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, 0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, 0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, 0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, -0.57735027f, 0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, -0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, -0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, -0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, -0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, 0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, 0.57735027f, -0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, 0.57735027f, 0.57735027f},
+    PointNormal {0.f, 0.f, 0.f, 0.57735027f, 0.57735027f, 0.57735027f},
+  };
+
+  // Fill container
+  auto cloud = pcl::make_shared<PointCloud<PointNormal>> ();
+  cloud->reserve (points.size ());
+  for (const auto& point : points)
+    cloud->push_back (point);
+
+  // pcl::Normal is not precompiled by default so we use PointNormal
   NormalSpaceSampling<PointNormal, PointNormal> normal_space_sampling;
-  normal_space_sampling.setInputCloud (cloud_walls_normals);
-  normal_space_sampling.setNormals (cloud_walls_normals);
-  normal_space_sampling.setBins (4, 4, 4);
+  normal_space_sampling.setInputCloud (cloud);
+  normal_space_sampling.setNormals (cloud);
+  normal_space_sampling.setBins (2, 2, 2);
   normal_space_sampling.setSeed (0);
-  normal_space_sampling.setSample (static_cast<unsigned int> (cloud_walls_normals->size ()) / 4);
+  normal_space_sampling.setSample (8);
 
-  IndicesPtr walls_indices (new std::vector<int> ());
+  IndicesPtr walls_indices  = pcl::make_shared<Indices> ();
   normal_space_sampling.filter (*walls_indices);
 
-  CovarianceSampling<PointNormal, PointNormal> covariance_sampling;
-  covariance_sampling.setInputCloud (cloud_walls_normals);
-  covariance_sampling.setNormals (cloud_walls_normals);
-  covariance_sampling.setIndices (walls_indices);
-  covariance_sampling.setNumberOfSamples (0);
-  double cond_num_walls_sampled = covariance_sampling.computeConditionNumber ();
-
+  // The orientation space of the normals is divided into 2x2x2 buckets
+  // points are samples arbitrarily from each bucket in succession until the
+  // requested number of samples is met. This means we expect to see only one index
+  // for every two elements in the original array e.g. 0, 3, 4, 6, etc...
+  // if 0 is sampled, index 1 can no longer be there and so forth
+  std::array<std::set<index_t>, 8> buckets;
+  for (const auto index : *walls_indices)
+    buckets[index/2].insert (index);
 
-  EXPECT_NEAR (33.04893, cond_num_walls_sampled, 1e-1);
 
-  EXPECT_EQ (1412, (*walls_indices)[0]);
-  EXPECT_EQ (1943, (*walls_indices)[walls_indices->size () / 4]);
-  EXPECT_EQ (2771, (*walls_indices)[walls_indices->size () / 2]);
-  EXPECT_EQ (3215, (*walls_indices)[walls_indices->size () * 3 / 4]);
-  EXPECT_EQ (2503, (*walls_indices)[walls_indices->size () - 1]);
+  EXPECT_EQ (8u, walls_indices->size ());
+  for (const auto& bucket : buckets)
+    EXPECT_EQ (1u, bucket.size ());
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////