class_docstr: Test the quality of DBSCAN clustering.
class_docstr_tok: ["Test","the","quality","of","DBSCAN","clustering","."]
docstr: Test what happens when there are no core points, boundary points, and
  noise points, respectively.
docstr_tok: ["Test","what","happens","when","there","are","no","core","points",",","boundary","points",",","and","noise","points",",","respectively","."]
code: def test_extreme_neighborhoods(self):
      """
      Test what happens when there are no core points, boundary points, and
      noise points, respectively.
      """
  
      ## Radius = 0 ==> all points are noise
      m = tc.dbscan.create(
          self.sf,
          distance="euclidean",
          radius=0.0,
          min_core_neighbors=3,
          verbose=False,
      )
  
      self.assertEqual(m.num_clusters, 0)
      self.assertEqual(sum(m.cluster_id["type"] == "noise"), self.n)
  
      ## Min_neighbors > 30 ==> all points are noise
      m = tc.dbscan.create(
          self.sf,
          distance="euclidean",
          radius=0.0,
          min_core_neighbors=31,
          verbose=False,
      )
  
      self.assertEqual(m.num_clusters, 0)
      self.assertEqual(sum(m.cluster_id["type"] == "noise"), self.n)
  
      ## Radius very large ==> all points are core points
      m = tc.dbscan.create(
          self.sf,
          distance="euclidean",
          radius=100.0,
          min_core_neighbors=3,
          verbose=False,
      )
  
      self.assertEqual(m.num_clusters, 1)
      self.assertEqual(sum(m.cluster_id["type"] == "core"), self.n)
  
      ## Min_neighbors = 0 ==> all points are core points
      m = tc.dbscan.create(
          self.sf,
          distance="euclidean",
          radius=0.5,
          min_core_neighbors=0,
          verbose=False,
      )
  
      self.assertEqual(m.num_clusters, 1)
      self.assertEqual(sum(m.cluster_id["type"] == "core"), self.n)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import copy
  import numpy
  import unittest
  import turicreate
  from .None import util
  from turicreate.util import _assert_sframe_equal
  from turicreate.toolkits._main import ToolkitError
  from .test_knn_classifier import make_classifier_data
  import sys
  import os
label_desc: Use image node_id 2 for calling the ResultsTest obj's underlying member method code with example usage: obj.test_extreme_neighborhoods() without return types