Merge pull request #9 from poncateam/correct_fields_sign

Correct fields sign

README.md

@@ -2,7 +2,28 @@
 2d plot application displaying scalar fields reconstructed using [Ponca](https://poncateam.github.io/ponca/)
 
 
+## Test different types of fits
 
+<img width="500" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/baddf074-6e32-447d-83aa-21d16fcd8977">
+<img width="500" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/aec9fa7c-ba5c-43b9-8953-56e8f8d2ed09">
+
+
+
+## Test different scales
+
+<img width="333" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/9d3e26b5-86f4-4248-965a-6fa0ed9497df">
+<img width="333" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/7b605409-a38e-45f6-a0d2-b3bcc1e3b17e">
+<img width="333" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/468eb5d9-711d-483e-a1af-ee6824905a57">
+
+## Change display options
+
+<img width="500" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/9b6497bb-c4c5-49e0-b42b-0a97d6fc37e6">
+<img width="500" alt="image" src="https://github.com/poncateam/poncaplot/assets/6310221/e4221532-d32a-479f-82d3-66e7b394e037">
+
+
+## Video
+
+(old version)
 
 https://github.com/poncateam/poncaplot/assets/6310221/a1885def-4135-4afa-b833-f2968697586f
 

src/dataManager.cpp

@@ -13,7 +13,7 @@ DataManager::savePointCloud(const std::string& path) const{
     if( ! file.is_open() ) return false;
 
     file << "# x y nx ny " << "\n";
-    for( const auto & p : m_tree.point_data() ){
+    for( const auto & p : m_tree.points() ){
         file << p.pos().transpose() << " " << p.normal().transpose() << "\n";
     }
     file.close();
@@ -80,7 +80,7 @@ DataManager::computeNormals(int k){
         // Set the evaluation position
         fit.init(p);
         // Fit plane (method compute handles multipass fitting
-        if (fit.computeWithIds(m_tree.k_nearest_neighbors(p, k), m_tree.point_data()) == Ponca::STABLE) {
+        if (fit.computeWithIds(m_tree.k_nearest_neighbors(p, k), m_tree.points()) == Ponca::STABLE) {
             pp.z() = std::acos(fit.primitiveGradient().normalized().x());
         } else
             std::cerr << "Something weird happened here..." << std::endl;
@@ -92,7 +92,7 @@ void
 DataManager::fitPointCloudToRange(const std::pair<float,float>& rangesEnd, const std::pair<float,float>& rangesStart){
     if (m_points.empty()) return;
     if (m_tree.node_count() == 0) updateKdTree();
-    auto aabb = m_tree.node_data()[0].getAabb();
+    auto aabb = m_tree.nodes()[0].getAabb();
     if (aabb){
         VectorType requestedSize {rangesEnd.first - rangesStart.first, rangesEnd.second - rangesStart.second};
         VectorType scaleFactors = requestedSize.array() / aabb->diagonal().array();

src/dataManager.h

@@ -57,7 +57,7 @@ struct MyKdTreeNode : Ponca::KdTreeCustomizableNode<Index, NodeIndex, DataPoint,
 struct DataManager {
 public:
 //    using KdTree = Ponca::KdTree<DataPoint>;
-    using KdTree = Ponca::KdTreeBase<Ponca::KdTreeDefaultTraits<DataPoint,MyKdTreeNode>>;
+    using KdTree = Ponca::KdTreeDenseBase<Ponca::KdTreeDefaultTraits<DataPoint,MyKdTreeNode>>;
     using PointContainer  = std::vector<nanogui::Vector3f>; // stores x,y,normal angle in radians
     using VectorType = typename KdTree::VectorType;
 

src/drawingPass.h

@@ -54,7 +54,7 @@ struct DisplayPoint : public DrawingPass {
         const auto pLargeSize = 2.f*m_halfSize;
 #pragma omp parallel for default(none) shared(points, buffer, w, h,pLargeSize)
         for (int pid = 0; pid< points.point_count(); ++pid){
-            const auto& p = points.point_data()[pid];
+            const auto& p = points.points()[pid];
             // Build vector that is orthogonal to the normal vector
             const VectorType& tangent {p.normal().y(), -p.normal().x()};
             int i (std::floor(p.pos().x()));

src/drawingPasses/distanceField.h

@@ -5,7 +5,7 @@
 struct DistanceField : public DrawingPass {
     inline explicit DistanceField() : DrawingPass() {}
     void render(const DataManager::KdTree& points, float*buffer, int w, int h) override {
-        if(points.point_data().empty())
+        if(points.points().empty())
         {
             buffer[1] = ColorMap::NO_FIELD;
             return;
@@ -17,7 +17,7 @@ struct DistanceField : public DrawingPass {
             for (int i = 0; i < w; ++i) {
                 auto *b = buffer + (i + j * w) * 4;
                 float minDist {float(w*h)};  //distance should necessarily be smaller
-                for (const auto &p : points.point_data()) {
+                for (const auto &p : points.points()) {
                     int u(std::floor(p.pos().x()));
                     int v(std::floor(p.pos().y()));
                     auto dist = float(std::sqrt((i-u)*(i-u) + (j-v)*(j-v)));
@@ -35,7 +35,7 @@ struct DistanceField : public DrawingPass {
 struct DistanceFieldWithKdTree : public DrawingPass {
     inline explicit DistanceFieldWithKdTree() : DrawingPass() {}
     void render(const DataManager::KdTree& points, float*buffer, int w, int h) override{
-        if(points.point_data().empty())
+        if(points.points().empty())
         {
             buffer[1] = ColorMap::NO_FIELD;
             return;
@@ -49,7 +49,7 @@ struct DistanceFieldWithKdTree : public DrawingPass {
                 DataPoint::VectorType query (i, j);
                 auto res = points.nearest_neighbor( query );
                 if(res.begin()!=res.end()) {
-                    auto nei = points.point_data()[res.get()].pos();
+                    auto nei = points.points()[res.get()].pos();
                     float dist = (nei-query).norm();
                     b[0] = dist;
                     b[2] = ColorMap::VALUE_IS_VALID;

src/drawingPasses/poncaFitField.h

@@ -22,7 +22,7 @@ struct FitField : public BaseFitField {
     virtual void postProcess(FitType& /*fit*/){};
 
     void render(const DataManager::KdTree& points, float*buffer, int w, int h) override{
-        if(points.point_data().empty()) return;
+        if(points.points().empty()) return;
 
         float maxVal = 0;
 #pragma omp parallel for collapse(2) default(none) shared(points, buffer, w, h) reduction(max : maxVal)
@@ -38,7 +38,7 @@ struct FitField : public BaseFitField {
                 for (int iter = 0; iter != m_iter; ++iter) {
                     fit.init(query);
                     // Fit plane (method compute handles multipass fitting
-                    if (fit.computeWithIds(points.range_neighbors(query, m_scale), points.point_data()) ==
+                    if (fit.computeWithIds(points.range_neighbors(query, m_scale), points.points()) ==
                         Ponca::STABLE) {
                         query = fit.project(query);
                     }
@@ -49,8 +49,8 @@ struct FitField : public BaseFitField {
                     float dist = fit.potential({i,j});
                     if (std::abs(dist)> maxVal) maxVal = std::abs(dist);
 
-                    b[0] = dist;                     // set pixel value
-                    b[3] = ColorMap::SCALAR_FIELD;   // set field type
+                    b[0] = fit.isSigned() ? dist : std::abs(dist);  // set pixel value
+                    b[3] = ColorMap::SCALAR_FIELD;                         // set field type
                 }
             }
         }