Merge pull request #6 from BianchTech/develop

feat: kNearestNeighbor and insert new point

Author: pedrobiqua

examples/main.cpp

@@ -3,21 +3,52 @@
 
 int main(int argc, char const *argv[])
 {
+    int x, y, k;
+    if (argc < 4) {
+        std::cerr << "Uso: " << argv[0] << " <x> <y> <k>\n";
+        x = 7;
+        y = 4;
+        k = 2;
+        // return 1;
+    } else {
+        x = std::atoi(argv[1]);
+        y = std::atoi(argv[2]);
+        k = std::atoi(argv[3]);
+    }
+
     std::vector<std::vector<int>> points = {
-        {1, 2, 3},
-        {2, 1, 3},
-        {3, 2, 1},
-        {7, 4, 0},
-        {5, 9, 2},
-        {6, 1, 8},
-        {0, 3, 5},
-        {4, 7, 6},
-        {8, 2, 9},
-        {3, 5, 7}
+        {1, 2},
+        {2, 1},
+        {3, 2},
+        {7, 4},
+        {5, 9},
+        {6, 1},
+        {0, 3},
+        {4, 7},
+        {8, 2},
+        {3, 5}
     };
 
     auto tree = new KDTree();
     tree->BuildTree(points);
     tree->PrintInorder();
+
+    std::vector<std::vector<int>> points_knn = tree->KNearestNeighbor({x, y}, k);
+
+    for (size_t i = 0; i < points_knn.size(); ++i) {
+        std::cout << "Point " << i << ": ";
+        for (size_t j = 0; j < points_knn[i].size(); ++j) {
+            std::cout << points_knn[i][j] << " ";
+        }
+        std::cout << std::endl;
+    }
+
+    std::cout << std::endl;
+    std::cout << std::endl;
+    std::cout << std::endl;
+
+    tree->Insert({x+1, y-1});
+    tree->PrintInorder();
+
     return 0;
 }

examples/plot_results.py

@@ -0,0 +1,33 @@
+import matplotlib.pyplot as plt
+
+# pontos fornecidos
+points = [
+    (1, 2),
+    (2, 1),
+    (3, 2),
+    (7, 4),
+    (5, 9),
+    (6, 1),
+    (0, 3),
+    (4, 7),
+    (8, 2),
+    (3, 5)
+]
+
+# separar em listas de x e y
+x_vals = [p[0] for p in points]
+y_vals = [p[1] for p in points]
+
+# plot
+plt.figure(figsize=(6,6))
+plt.scatter(x_vals, y_vals, color="blue")
+
+# adicionar labels
+for (x, y) in points:
+    plt.text(x+0.1, y+0.1, f"({x},{y})", fontsize=8)
+
+plt.xlabel("x")
+plt.ylabel("y")
+plt.title("Plot dos pontos fornecidos")
+plt.grid(True)
+plt.show()

include/mlcpppy/classifiers/neighbors/kdtree.h

@@ -18,22 +18,29 @@
 #define KDTREE_H
 
 #include <vector>
+#include <queue>
 #include "nearest_neighbor.h"
 
 class KDTree : public NearestNeighbor {
  private:
-  std::vector<std::vector<int>> points;
   class Node;
-  Node* root;
+  Node* root_;
+  int K_;
+  std::priority_queue<std::pair<double, Node*>> bests_;
+
   Node* Build(std::vector<std::vector<int>> points, int depth);
+  Node* NearestNeighbor(Node* root, std::vector<int>& target, int depth);
+  void KNearestNeighbor(Node* root, std::vector<int>& target, int depth);
+
+  Node* Closest(Node* n0, Node* n1, std::vector<int>& target);
+  double DistSquared(const std::vector<int>& p0, const std::vector<int>& p1);
   static void Inorder(Node* root);
 
  public:
   KDTree();
   void Insert(std::vector<int> point) override;
   void BuildTree(std::vector<std::vector<int>> points) override;
-  std::vector<std::vector<int>> KNearestNeighbor(std::vector<int> target_points,
-                                                 int k) override;
+  std::vector<std::vector<int>> KNearestNeighbor(std::vector<int> target_points, int k) override;
   void PrintInorder();
 
   ~KDTree() override;