docstr: This function performs all initializations necessary:
  load the data sets and set the training set indices and response column index
docstr_tok: ["This","function","performs","all","initializations","necessary",":","load","the","data","sets","and","set","the","training","set","indices","and","response","column","index"]
code: def setup_data(self):
      """
      This function performs all initializations necessary:
      load the data sets and set the training set indices and response column index
      """
      self.h2o_data = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/glm_test/gaussian_20cols_10000Rows.csv"
          )
      )
      self.h2o_data["C1"] = self.h2o_data["C1"].asfactor()
      self.h2o_data["C2"] = self.h2o_data["C2"].asfactor()
      self.myX = ["C1", "C2"]
      self.myY = "C21"
      for scale in self.hyper_parameters["scale"]:
          for gam_columns in self.hyper_parameters["gam_columns"]:
              for lambda_ in self.hyper_parameters["lambda"]:
                  self.manual_gam_models.append(
                      H2OGeneralizedAdditiveEstimator(
                          family="gaussian",
                          gam_columns=gam_columns,
                          keep_gam_cols=True,
                          scale=scale,
                          lambda_=lambda_,
                      )
                  )
  
file_path: h2o-3/h2o-py/tests/testdir_algos/gam/pyunit_PUBDEV_7367_random_gridsearch_generic.py
imports: from past.utils import old_div
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gam import H2OGeneralizedAdditiveEstimator
  from h2o.grid.grid_search import H2OGridSearch
label_desc: Use image node_id 2 for calling the test_random_gam_gridsearch_generic obj's underlying member method code with example usage: obj.setup_data() without return types