code: def test_plot_predicted_data(iclaims_training_data, plot_components):
      df = iclaims_training_data
      df["claims"] = np.log(df["claims"])
  
      regressor_col = ["trend.unemploy", "trend.filling", "trend.job"]
      test_size = 52
      train_df = df[:-test_size]
      test_df = df[-test_size:]
  
      lgt = LGT(
          response_col="claims",
          date_col="week",
          regressor_col=regressor_col,
          estimator="stan-map",
          seasonality=52,
          seed=8888,
      )
      lgt.fit(train_df)
      predicted_df = lgt.predict(df=test_df, decompose=True)
  
      # test plotting
      _ = plot_predicted_data(
          training_actual_df=train_df,
          predicted_df=predicted_df,
          date_col="week",
          actual_col="claims",
          test_actual_df=test_df,
      )
  
      _ = plot_predicted_components(
          predicted_df=predicted_df,
          date_col="week",
          plot_components=plot_components,
      )
  
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 1 for calling a global function with example usage: test_plot_predicted_data(iclaims_training_data, plot_components) without return types