code: def test_plots(self):
      arena = dx.Arena()
      arena.push_model(self.exp)
      arena.push_observations(self.X.iloc[[1],])
      arena.set_option("DatasetShapleyValues", "N", 10)
      arena.plots_manager.fill_cache()
      for p in self.reference_plots:
          ref_counts = list(
              map(
                  lambda param_type: len(arena.list_params(param_type)),
                  p.info.get("requiredParams"),
              )
          )
          count = np.sum(
              [
                  1
                  for plot in arena.plots_manager.cache
                  if plot.__class__ == p
              ]
          )
          self.assertEqual(
              np.prod(ref_counts), count, msg="Count of " + str(p)
          )
  
imports: import unittest
  from plotly.graph_objs import Figure
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  import dalex
  import time
  import numpy
  import pandas
  from dalex.arena.static import get_free_port, try_port
  from dalex.arena.plots import *
label_desc: Use image node_id 4 for calling the ArenaTestTitanic obj's underlying member method code with example usage: obj.test_plots() without return types