code: def test_retrieval(self):
      # We want 12 projections, 20 results at least
      rbpt = RandomBinaryProjectionTree("testHash", 12, 20)
  
      # Create engine for 100 dimensional feature space, do not forget to set
      # nearest filter to 20, because default is 10
      self.engine = Engine(
          100, lshashes=[rbpt], vector_filters=[NearestFilter(20)]
      )
  
      # First insert 200000 random vectors
      for k in range(200000):
          x = numpy.random.randn(100)
          x_data = "data {}".format(k)
          self.engine.store_vector(x, x_data)
  
      # Now do random queries and check result set size
      for k in range(10):
          x = numpy.random.randn(100)
          n = self.engine.neighbours(x)
          self.assertEqual(len(n), 20)
  
file_path: NearPy/tests/projection_trees_tests.py
imports: import unittest
  import functools
  import numpy
  from nearpy import Engine
  from nearpy.filters import NearestFilter
  from nearpy.hashes import RandomBinaryProjectionTree
  from mockredis import MockRedis
  from nearpy.storage import MemoryStorage, RedisStorage
label_desc: Use image node_id 2 for calling the TestRandomBinaryProjectionTree obj's underlying member method code with example usage: obj.test_retrieval() without return types