class_docstr: Class to test the AutoML flow
      
class_docstr_tok: ["Class","to","test","the","AutoML","flow"]
docstr: test to check functionality Prophet with CV
docstr_tok: ["test","to","check","functionality","Prophet","with","CV"]
code: def test_prophet_multivar_standalone_with_cv(self):
      """
      test to check functionality Prophet with CV
      """
      print("\n\n" + "*" * 50)
      print(
          "Performing Unit Test: 'test_prophet_multivar_standalone_withCV'"
      )
      print("*" * 50 + "\n\n")
  
      # import numpy as np  # type: ignore
      # from auto_ts import auto_timeseries as ATS
  
      automl_model = ATS(
          score_type="rmse",
          forecast_period=self.forecast_period,
          time_interval="Month",
          non_seasonal_pdq=None,
          seasonality=False,
          seasonal_period=12,
          model_type=["prophet"],
          verbose=0,
      )
      automl_model.fit(
          traindata=self.train_multivar,
          ts_column=self.ts_column,
          target=self.target,
          cv=2,
          sep=self.sep,
      )
  
      ml_dict = automl_model.get_ml_dict()
  
      ####################################
      #### Internal Validation Checks ####
      ####################################
  
      ## Validation Forecast
      self.assertIsNone(
          np.testing.assert_array_equal(
              np.round(
                  ml_dict.get("Prophet").get("forecast")[0]["yhat"], 6
              ),
              self.forecast_gold_prophet_multivar_internal_val_cv_fold1,
          )
      )
      self.assertIsNone(
          np.testing.assert_array_equal(
              np.round(
                  ml_dict.get("Prophet").get("forecast")[1]["yhat"], 6
              ),
              self.forecast_gold_prophet_multivar_internal_val_cv_fold2,
          )
      )
  
      # Validation RMSE
      self.assertEqual(
          round(ml_dict.get("Prophet").get("rmse")[0], 8),
          self.rmse_gold_prophet_multivar_cv_fold1,
      )
      self.assertEqual(
          round(ml_dict.get("Prophet").get("rmse")[1], 8),
          self.rmse_gold_prophet_multivar_cv_fold2,
      )
  
      ##############################
      #### External Test Checks ####
      ##############################
  
      # Simple forecast with forecast window = one used in training
      # Using named model
      test_predictions = automl_model.predict(
          testdata=self.test_multivar[[self.ts_column] + self.preds],
          forecast_period=self.forecast_period,
          model="Prophet",
      )
      assert_series_equal(
          test_predictions["yhat"].round(6),
          self.forecast_gold_prophet_multivar_external_test_cv,
      )
  
      # Simple forecast with forecast window != one used in training
      # Using named model
      test_predictions = automl_model.predict(
          testdata=self.test_multivar[[self.ts_column] + self.preds],
          forecast_period=10,
          model="Prophet",
      )
      assert_series_equal(
          test_predictions["yhat"].round(6),
          self.forecast_gold_prophet_multivar_external_test_10_cv,
      )
  
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 prophet.forecaster import Prophet
  from statsmodels.tsa.statespace.sarimax import SARIMAXResultsWrapper
  from sklearn.base import BaseEstimator
  from auto_ts import auto_timeseries
label_desc: Use image node_id 10 for calling the TestAutoTS obj's underlying member method code with example usage: obj.test_prophet_multivar_standalone_with_cv() without return types