text: import matplotlib.pyplot as plt
  import os
  root_path = os.path.dirname(os.path.abspath('__file__'))
  import sys
  sys.path.append(root_path)
  from tools.models import one_step_esvr,one_step_esvr_multi_seed
  
  
  if __name__ == '__main__':
      for cv in range(2,11):
          one_step_esvr(
              root_path=root_path,
              station='Huaxian',
              decomposer='ssa',
              predict_pattern='one_step_1_ahead_forecast_pacf',# hindcast or forecast or hindcast_with_pca_mle or forecast_with_pca_mle
              n_calls=100,
              cv=cv,
          )
  
      # for leading_time in [3,5,7,9]:
      #     one_step_esvr_multi_seed(
      #         root_path=root_path,
      #         station='Huaxian',
      #         decomposer='ssa',
      #         predict_pattern='one_step_'+str(leading_time)+'_month_forecast_0.3',# hindcast or forecast or hindcast_with_pca_mle or forecast_with_pca_mle
      #         n_calls=100,
      #     )
      
      # for i in range(40,55):
          # one_step_esvr_multi_seed(
          #     root_path=root_path,
          #     station='Huaxian',
          #     decomposer='ssa',
          #     predict_pattern='one_step_9_month_forecast',#+str(i),# hindcast or forecast or hindcast_with_pca_mle or forecast_with_pca_mle
          #     n_calls=100,
          # )