Merge branch 'poncateam:master' into add_mean_plane

CHANGELOG

@@ -4,6 +4,20 @@ Ponca changelog
 
 --------------------------------------------------------------------------------
 Current head (v.1.1 RC)
+This release improves the Spatial Partitioning Package with new features and
+improved doc.
+
+- API
+    - [spatialPartitioning] Add kd-tree traits type (#80)
+    - [fitting] Add Primitive::getNumNeighbors (#86)
+
+- Bug-fixes and code improvements
+    - [spatialPartitioning] Fix unwanted function hiding with DryFit::setWeightFunc (#86)
+    - [fitting] Remove deadcode in Basket (#86)
+
+-Docs
+    - [spatialPartitioning] Update module page with a minimal doc and examples (#86)
+    - [spatialPartitioning] Add NanoFlann example (#86)
 
 --------------------------------------------------------------------------------
 v.1.0
@@ -28,7 +42,6 @@ The changes introduced in this version mostly are introduced by PR #56.
     - [fitting] Rename normal() as primitiveGradient in MlsSphereFit (#72)
     - [fitting] Add new weight kernels (#71,#74)
     - [fitting] Add mechanism to check weight derivatives validity (#74)
-    - [spatialPartitioning] Add kd-tree traits type (#80)
 
 - Bug-fixes and code improvements
     - [fitting] Reduce objets sizes by removing unnecessary attributes (#56)

Ponca/src/Fitting/basket.h

@@ -64,13 +64,13 @@ namespace internal
     PONCA_MULTIARCH inline                                                                            \
     FIT_RESULT computeWithIds(IndexRange ids, const PointContainer& points){                          \
         FIT_RESULT res = UNDEFINED;                                                                   \
-            do {                                                                                      \
-                for (const auto& i : ids){                                                            \
-                    this->addNeighbor(points[i]);                                                     \
-                }                                                                                     \
-                res = this->finalize();                                                               \
-            } while ( res == NEED_OTHER_PASS );                                                       \
-            return res;return Self::computeWithIds(ids, points);                                      \
+        do {                                                                                          \
+            for (const auto& i : ids){                                                                \
+                this->addNeighbor(points[i]);                                                         \
+            }                                                                                         \
+            res = this->finalize();                                                                   \
+        } while ( res == NEED_OTHER_PASS );                                                           \
+        return res;                                                                                   \
     }                                                                                                 \
     WRITE_BASKET_SINGLE_HOST_FUNCTIONS
 

Ponca/src/Fitting/dryFit.h

@@ -37,9 +37,6 @@ namespace Ponca
         PONCA_FITTING_APIDOC_FINALIZE
         PONCA_MULTIARCH inline FIT_RESULT finalize() { return Base::finalize(); }
 
-        PONCA_FITTING_APIDOC_SETWFUNC
-        PONCA_MULTIARCH inline void setWeightFunc (const WFunctor& /*_w*/) { }
-
         //! \brief Simulate Scalar field computation
         PONCA_MULTIARCH inline Scalar potential ( ) const { return Scalar(0); }
 

Ponca/src/Fitting/primitive.h

@@ -83,6 +83,9 @@ class PrimitiveBase
     and the result is stable, eq. having more than 6 neighbors) */
     PONCA_MULTIARCH inline bool isStable() const { return m_eCurrentState == STABLE; }
 
+    /*! \brief Get number of points added in the neighborhood (with non negative weight)  */
+     PONCA_MULTIARCH inline int getNumNeighbors() const { return m_nbNeighbors; }
+
     /*! \return the current test of the fit */
     PONCA_MULTIARCH inline FIT_RESULT getCurrentState() const
     {

doc/src/example.mdoc

@@ -17,5 +17,7 @@
     - \subpage example_cxx_pcl_page : How to use Ponca with Point cloud library (PCL). A basic example to compute and visualize surface curvature.
     - \subpage example_cu_ssc_page : Calculate Screen Space Curvature using CUDA/C++.
     - \subpage example_python_ssc_page : Calculate Screen Space Curvature using CUDA/Python.
+  - @ref spatialpartitioning "Spatial Partitioning Module"
+    - \subpage example_cxx_nanoflann_page : Comparison between Nanoflann and Ponca KdTree APIs.
 
  */

doc/src/example_cxx_nanoflann.mdoc

@@ -0,0 +1,53 @@
+/*
+ This Source Code Form is subject to the terms of the Mozilla Public
+ License, v. 2.0. If a copy of the MPL was not distributed with this
+ file, You can obtain one at http://mozilla.org/MPL/2.0/.
+*/
+
+
+/*!
+  \page example_cxx_nanoflann_page Comparison between Nanoflann and Ponca KdTree APIs
+
+  \section nanoflann_intro_sec Introduction
+
+  This example demonstrates how to use Ponca and <a href="https://github.com/jlblancoc/nanoflann" target="_blank">
+  Nanoflann</a> (v1.5.0) KdTrees on the same data, and compare runtime performances.
+
+  \subsection nanoflann_compilation_sec Compilation
+
+  As for other examples, you need to enable the compilation of the examples with `cmake`, and build the examples:
+
+  \code
+  cmake [..] -DPONCA_CONFIGURE_EXAMPLES=ON
+  make ponca-examples // or make ponca_nanoflann
+  \endcode
+
+  \section nanoflann_comparison_sec API comparisons
+
+  Task             | Ponca                                                 | Nanoflann
+  ---------------- | ----------------------------------------------------- | -------------
+  KdTree Creation  | \snippet ponca_nanoflann.cpp Create Ponca KdTree      | \snippet ponca_nanoflann.cpp Create NanoFlann KdTree
+  Range Query      | \snippet ponca_nanoflann.cpp Use Ponca KdTree  | \snippet ponca_nanoflann.cpp Use NanoFlann KdTree
+
+  The fitting object is a Ponca::DryFit, an object that filter the neighbors according to their weight (out of scale points
+  are not counted), but do not perform any other computation:
+  \snippet ponca_nanoflann.cpp Define Fit Type
+
+  \section nanoflann_timings_sec Timings
+  The example output the time required to collect the neighbors, and the number of neighbors collected:
+  \code
+Timings:
+Raw :       0.168698
+Ponca :     0.025475
+Nanoflann : 0.027746
+Number of neighbors:
+Raw :       950618
+Ponca :     950618
+Nanoflann : 950618
+  \endcode
+
+  \section nanoflann_sourcecode_sec Example source code
+  Source file: `ponca_nanoflann.cpp`
+  \include ponca_nanoflann.cpp
+
+ */

doc/src/ponca_module_spatialpartitioning.mdoc

@@ -42,7 +42,13 @@ namespace Ponca
   \note As queries are objets that are independent from the KdTree, they can be created and used in parallel from
   multiple threads.
 
-
+  \subsection spatialpartitioning_kdtree_examples Examples
+  KdTree usage is demonstrated both in tests and examples:
+   - `tests/src/basket.cpp`
+   - `tests/src/kdtree_knearest.cpp`
+   - `tests/src/kdtree_nearest.cpp`
+   - `tests/src/kdtree_range.cpp`
+   - `examples/cpp/nanoflann/ponca_nanoflann.cpp`
 
   \subsection spatialpartitioning_kdtree_extending Extending KdTree
   Ponca::KdTreeBase is a customizable version of Ponca::KdTree, which can be controlled using `Traits`.

examples/cpp/CMakeLists.txt

@@ -35,3 +35,4 @@ add_dependencies(ponca-examples ponca_fit_line)
 ponca_handle_eigen_dependency(ponca_fit_line)
 
 add_subdirectory(pcl)
+add_subdirectory(nanoflann)

examples/cpp/nanoflann/CMakeLists.txt

@@ -0,0 +1,8 @@
+project(Ponca_Example_Nanoflann LANGUAGES CXX)
+
+set(CMAKE_INCLUDE_CURRENT_DIR ON)
+
+add_executable(ponca_nanoflann ponca_nanoflann.cpp)
+target_include_directories(ponca_nanoflann PRIVATE ${PONCA_src_ROOT})
+add_dependencies(ponca-examples ponca_nanoflann)
+ponca_handle_eigen_dependency(ponca_nanoflann)