class_docstr: Test the create method for DBSCAN clustering.
class_docstr_tok: ["Test","the","create","method","for","DBSCAN","clustering","."]
code: def setUpClass(self):
      ## Data generated by np.random.seed(31); tc.SFrame(np.random.rand(30, 2))
      self.sf = tc.SFrame(
          {
              "X1": [
                  [0.286053821661, 0.958105566519],
                  [0.770312932219, 0.986870003092],
                  [0.208165461905, 0.136917048844],
                  [0.90837380229, 0.0686385179771],
                  [0.0753327223397, 0.543534689487],
                  [0.0893997165181, 0.382393267526],
                  [0.668560439681, 0.429169022562],
                  [0.0439563074864, 0.194285988749],
                  [0.446659483973, 0.062573278102],
                  [0.297567282015, 0.943630899918],
                  [0.282811075761, 0.267693546553],
                  [0.407219004134, 0.825990402953],
                  [0.506700663192, 0.269475381046],
                  [0.340188287419, 0.97447185149],
                  [0.18430457912, 0.242272172626],
                  [0.6904593137, 0.383935276414],
                  [0.461442452896, 0.675224987045],
                  [0.0857306038525, 0.234016647286],
                  [0.522458878224, 0.0691166755345],
                  [0.0902366982884, 0.0839678579833],
                  [0.3228005527, 0.910903399861],
                  [0.831990012991, 0.75008026969],
                  [0.469253814747, 0.867324370425],
                  [0.279287904686, 0.0816360972888],
                  [0.14921147693, 0.494767544759],
                  [0.303711931037, 0.301766873086],
                  [0.007386922447, 0.579463366777],
                  [0.718318063984, 0.407263481941],
                  [0.162964200289, 0.210306678644],
                  [0.760123026079, 0.357788149323],
              ]
          }
      )
  
      self.min_core_neighbors = 3
      self.radius = 0.3
      self.distance = [[["X1"], "euclidean", 1]]
      self.model = tc.dbscan.create(
          self.sf,
          distance=self.distance,
          radius=self.radius,
          min_core_neighbors=self.min_core_neighbors,
          verbose=False,
      )
  
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 1 for calling the CreateTest obj's underlying member method code with example usage: obj.setUpClass() without return types