Use Heap to query multiples neighbours

kdtree/query_poc.py

+import numpy as np
+import pytest
+import kdtree
+from sklearn.neighbors import KDTree
+
+if __name__ == '__main__':
+    
+    n = 1000
+    n_query = 100
+    d = 10
+    k = 10
+     
+    np.random.seed(1)
+    X = np.random.rand(n, d)
+    query_points = np.random.rand(n_query, d)
+
+    tree = kdtree.KDTree(X, leaf_size=256)
+    closests = np.zeros((n_query, k), dtype=np.int32)
+    
+    # There's currently a deadlock here
+    tree.query(query_points, closests)
\ No newline at end of file

kdtree/tests/test_conf.py

@@ -14,8 +14,8 @@ def test_against_sklearn(n, d, leaf_size):
     tree = kdtree.KDTree(X, leaf_size=256)
     skl_tree = KDTree(X, leaf_size=256)
     
-    closests = np.zeros((n), dtype=np.int32)
-    tree.get_closest(query_points, closests)
+    closests = np.zeros((n, 2), dtype=np.int32)
+    tree.query(query_points, closests)
     skl_closests = skl_tree.query(query_points, return_distance=False)
     
     # The back tracking part of the algorithm is not yet implemented