code: def setUp(self):
      # Pre Release
  
      datapath = "example_datasets/"
      filename1 = "Sales_and_Marketing.csv"
      dft = pd.read_csv(datapath + filename1, index_col=None)
  
      self.ts_column = "Time Period"
      self.sep = ","
      self.target = "Sales"
      self.preds = [
          x for x in list(dft) if x not in [self.ts_column, self.target]
      ]  # Exogenous variable names
  
      self.train_multivar = dft[:40]
      self.test_multivar = dft[40:]
  
      self.train_univar = dft[:40][[self.ts_column, self.target]]
      self.test_univar = dft[40:][[self.ts_column, self.target]]
  
      self.forecast_period = 8
  
      self.expected_pred_col_names = np.array(
          ["mean", "mean_se", "mean_ci_lower", "mean_ci_upper"]
      )
  
      ########################
      #### Golden Results ####
      ########################
  
      # TODO: Add to each individual test
      ## For each of the 8 combinations, we need the following
      # Internal Validation results (for each fold)
      # Internal Validation RMSE (overall and for each fold)
  
      # External Test results (various combinations of prediction windows - same as forecast period OR not same)
      # External Test RMSE
  
      ############################
      #### VAR Golden Results ####
      ############################
  
      #### UNIVARIATE ####
      self.forecast_gold_var_univar = None
      self.rmse_gold_var_univar = math.inf
      self.forecast_gold_var_univar_series = None
      self.forecast_gold_var_univar_series_10 = None
  
      #### MULTIVARIATE ####
  
      # Internal (to AutoML) validation set results
      self.forecast_gold_var_multivar_internal_val_cv_fold1 = np.array(
          [
              510.302336,
              531.109224,
              536.878513,
              534.311164,
              529.305887,
              525.199071,
              523.015255,
              522.445215,
          ]
      )
  
      self.forecast_gold_var_multivar_internal_val_cv_fold2 = np.array(
          [
              741.377909,
              676.233419,
              615.538721,
              571.797729,
              546.952783,
              537.342231,
              537.474487,
              542.307393,
          ]
      )
  
      self.rmse_gold_var_multivar_cv_fold1 = 155.21757611
      self.rmse_gold_var_multivar_cv_fold2 = (
          112.4770318  # Without CV gets this result
      )
  
      ## External Test Set results
      results = [
          675.899931,
          622.204059,
          578.38291,
          553.067517,
          543.612945,
          543.696406,
          547.604403,
          551.762352,
      ]
      index = pd.to_datetime(
          [
              "2014-05-01",
              "2014-06-01",
              "2014-07-01",
              "2014-08-01",
              "2014-09-01",
              "2014-10-01",
              "2014-11-01",
              "2014-12-01",
          ]
      )
      self.forecast_gold_var_multivar = np.array(results)
  
      self.forecast_gold_var_multivar_series = pd.Series(
          data=results, index=index
      )
      self.forecast_gold_var_multivar_series.name = "mean"
  
      results = results + [554.643756, 556.055009]
      index = pd.to_datetime(
          [
              "2014-05-01",
              "2014-06-01",
              "2014-07-01",
              "2014-08-01",
              "2014-09-01",
              "2014-10-01",
              "2014-11-01",
              "2014-12-01",
              "2015-01-01",
              "2015-02-01",
          ]
      )
      self.forecast_gold_var_multivar_series_10 = pd.Series(
          data=results, index=index
      )
      self.forecast_gold_var_multivar_series_10.name = "mean"
  
file_path: Auto_TS/auto_ts/test/test_var.py
imports: import sys
  import os
  import unittest
  import math
  import numpy
  import pandas
  from pandas.testing import assert_series_equal
  from pandas.testing import assert_frame_equal
  from statsmodels.tsa.statespace.sarimax import SARIMAXResultsWrapper
  from auto_ts import auto_timeseries
label_desc: Use image node_id 1 for calling the TestVAR obj's underlying member method code with example usage: obj.setUp() without return types