Clarify normal construction strategy.

Co-Authored-By: Kunal Tyagi <tyagi.kunal@live.com>

Author: SergioRAgostinho

test/filters/test_sampling.cpp

@@ -105,33 +105,21 @@ 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
+  // pcl::Normal is not precompiled by default so we use PointNormal
   auto cloud = pcl::make_shared<PointCloud<PointNormal>> ();
-  cloud->reserve (points.size ());
-  for (const auto& point : points)
-    cloud->push_back (point);
+  // generate 16 points (8 unique) with unit norm
+  cloud->reserve (16);
+  // ensure that the normals have unit norm
+  const auto value = std::sqrt(1/3.f);
+  for (int unique = 0; unique < 8; ++unique) {
+    const auto i = ((unique % 2) < 1) ? -1 : 1;  // points alternate sign
+    const auto j = ((unique % 4) < 2) ? -1 : 1;  // 2 points negative, 2 positive
+    const auto k = ((unique % 8) < 4) ? -1 : 1;  // first 4 points negative, rest positive
+    for (int duplicate = 0; duplicate < 2; ++duplicate) {
+      cloud->emplace_back (0.f, 0.f, 0.f, i * value,  j * value, k * value);
+    }
+  }
 
-  // pcl::Normal is not precompiled by default so we use PointNormal
   NormalSpaceSampling<PointNormal, PointNormal> normal_space_sampling;
   normal_space_sampling.setInputCloud (cloud);
   normal_space_sampling.setNormals (cloud);