code: def test_plot_model_customization(data):
      """Tests the customization of plot_model
      NOTE: Want to show multiplicative plot here so can not take data with negative values
      """
      exp = TSForecastingExperiment()
  
      fh = np.arange(1, 13)
      fold = 2
  
      exp.setup(
          data=data,
          fh=fh,
          fold=fold,
          fold_strategy="sliding",
          verbose=False,
          session_id=42,
      )
  
      model = exp.create_model("naive")
  
      #######################
      # Customization ####
      #######################
  
      print("\n\n==== Testing Customization ON DATA ====")
      exp.plot_model(
          plot="pacf",
          data_kwargs={
              "nlags": 36,
          },
          fig_kwargs={
              "fig_size": [800, 500],
              "fig_template": "simple_white",
          },
      )
      exp.plot_model(
          plot="decomp_classical",
          data_kwargs={"type": "multiplicative"},
      )
  
      print("\n\n====  Testing Customization ON ESTIMATOR ====")
      exp.plot_model(
          estimator=model, plot="forecast", data_kwargs={"fh": 24}
      )
  
file_path: pycaret/tests/test_time_series_plots.py
imports: import os
  import sys
  import numpy
  import pytest
  from time_series_test_utils import _ALL_PLOTS_DATA, _ALL_PLOTS_ESTIMATOR, _ALL_PLOTS_ESTIMATOR_NOT_DATA, _return_all_plots_estimator_ts_results, _return_data_with_without_period_index, _return_model_names_for_plots_stats
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 4 for calling a global function with example usage: test_plot_model_customization(data) without return types