code: def test_quadtree_similar_point():
      # Introduce a point into a quad tree where a similar point already exists.
      # Test will hang if it doesn't complete.
      Xs = []
  
      # check the case where points are actually different
      Xs.append(np.array([[1, 2], [3, 4]], dtype=np.float32))
      # check the case where points are the same on X axis
      Xs.append(np.array([[1.0, 2.0], [1.0, 3.0]], dtype=np.float32))
      # check the case where points are arbitrarily close on X axis
      Xs.append(
          np.array([[1.00001, 2.0], [1.00002, 3.0]], dtype=np.float32)
      )
      # check the case where points are the same on Y axis
      Xs.append(np.array([[1.0, 2.0], [3.0, 2.0]], dtype=np.float32))
      # check the case where points are arbitrarily close on Y axis
      Xs.append(
          np.array([[1.0, 2.00001], [3.0, 2.00002]], dtype=np.float32)
      )
      # check the case where points are arbitrarily close on both axes
      Xs.append(
          np.array(
              [[1.00001, 2.00001], [1.00002, 2.00002]], dtype=np.float32
          )
      )
  
      # check the case where points are arbitrarily close on both axes
      # close to machine epsilon - x axis
      Xs.append(
          np.array(
              [[1, 0.0003817754041], [2, 0.0003817753750]],
              dtype=np.float32,
          )
      )
  
      # check the case where points are arbitrarily close on both axes
      # close to machine epsilon - y axis
      Xs.append(
          np.array(
              [[0.0003817754041, 1.0], [0.0003817753750, 2.0]],
              dtype=np.float32,
          )
      )
  
      for X in Xs:
          tree = _QuadTree(n_dimensions=2, verbose=0)
          tree.build_tree(X)
          tree._check_coherence()
  
file_path: scikit-learn/sklearn/neighbors/tests/test_quad_tree.py
imports: import pickle
  import numpy
  import pytest
  from sklearn.neighbors._quad_tree import _QuadTree
  from sklearn.utils import check_random_state
label_desc: Use image node_id 2 for calling a global function with example usage: test_quadtree_similar_point() without return types