code: def test_plot_bt_predictions(iclaims_training_data):
      df = iclaims_training_data
      df["claims"] = np.log(df["claims"])
  
      regressor_col = ["trend.unemploy", "trend.filling", "trend.job"]
  
      dlt = DLT(
          date_col="week",
          response_col="claims",
          regressor_col=regressor_col,
          seasonality=52,
          estimator="stan-map",
      )
      bt = BackTester(
          model=dlt,
          df=df,
          min_train_len=100,
          incremental_len=100,
          forecast_len=20,
      )
      bt.fit_predict()
      predicted_df = bt.get_predicted_df()
  
      # test plotting
      _ = plot_bt_predictions(
          predicted_df, metrics=smape, ncol=2, include_vline=True
      )
      _ = plot_bt_predictions2(
          predicted_df, metrics=smape, include_vline=True
      )
  
file_path: orbit/tests/orbit/diagnostics/test_plot.py
imports: import pytest
  import pandas
  import numpy
  from orbit.diagnostics.backtest import BackTester
  from orbit.diagnostics.metrics import smape
  from orbit.models import LGT, DLT
  from orbit.diagnostics.plot import plot_predicted_data, plot_predicted_components, plot_bt_predictions, plot_bt_predictions2
label_desc: Use image node_id 2 for calling a global function with example usage: test_plot_bt_predictions(iclaims_training_data) without return types