code: def setUp(self):
      self.data = [0] * 9 + [1] + [0] * 10
      self.data5 = range(100)
      self.dlm3 = _dlmPredict(
          [-1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1]
      )
      self.dlm4 = _dlmPredict([0, 0, 0, 0, 0, 1, 1, 1, 1, 1])
      self.dlm5 = _dlmPredict(self.data5)
  
      self.dlm3.builder + seasonality(period=2, discount=1, w=1.0)
      self.dlm4.builder + dynamic(
          features=[[0] for i in range(5)] + [[1] for i in range(5)],
          discount=1,
          w=1.0,
      )
      (
          self.dlm5.builder
          + trend(degree=0, discount=1, w=1.0)
          + autoReg(degree=1, discount=1, w=1.0)
      )
  
      self.dlm3._initialize()
      self.dlm4._initialize()
      self.dlm5._initialize()
  
      self.dlm3.options.innovationType = "whole"
      self.dlm4.options.innovationType = "whole"
      self.dlm5.options.innovationType = "whole"
  
file_path: pydlm/tests/predict/test_dlmPredict.py
imports: import unittest
  from pydlm.modeler.trends import trend
  from pydlm.modeler.seasonality import seasonality
  from pydlm.modeler.dynamic import dynamic
  from pydlm.modeler.autoReg import autoReg
  from pydlm.predict._dlmPredict import _dlmPredict
label_desc: Use image node_id 1 for calling the test_dlmPredict obj's underlying member method code with example usage: obj.setUp() without return types