code: def test(self):
      self.assertIsInstance(self.aspect.explainer, dx.Explainer)
      self.assertIsInstance(self.aspect2.explainer, dx.Explainer)
  
      self.assertIsInstance(self.aspect.depend_matrix, pd.DataFrame)
      self.assertIsInstance(self.aspect2.depend_matrix, pd.DataFrame)
      pd.testing.assert_frame_equal(
          self.aspect2.depend_matrix, self.aspect2.depend_matrix.T
      )
      for ind, row in self.aspect.depend_matrix.iterrows():
          self.assertEqual(row[ind], 1.0)
      for ind, row in self.aspect2.depend_matrix.iterrows():
          self.assertEqual(row[ind], 1.0)
  
      self.assertIsInstance(self.aspect.linkage_matrix, np.ndarray)
      self.assertIsInstance(self.aspect2.linkage_matrix, np.ndarray)
  
      self.assertIsInstance(
          self.aspect._hierarchical_clustering_dendrogram, Figure
      )
      self.assertIsInstance(
          self.aspect2._hierarchical_clustering_dendrogram, Figure
      )
  
      self.assertIsInstance(
          self.aspect._dendrogram_aspects_ordered, pd.DataFrame
      )
      self.assertIsInstance(
          self.aspect2._dendrogram_aspects_ordered, pd.DataFrame
      )
  
      self.assertIsInstance(self.aspect.get_aspects(h=0.3), dict)
      self.assertIsInstance(self.aspect2.get_aspects(h=0.99), dict)
      self.assertGreaterEqual(
          3, len(self.aspect.get_aspects(h=0.3, n=3))
      )
      self.assertEqual(
          len(self.aspect.depend_matrix),
          len(self.aspect2.get_aspects(h=3)),
      )
  
      self.assertIsInstance(
          self.aspect.plot_dendrogram(show=False), Figure
      )
      self.assertIsInstance(
          self.aspect2.plot_dendrogram(show=False), Figure
      )
  
imports: import unittest
  import numpy
  import pandas
  from plotly.graph_objs import Figure
  from ipywidgets.widgets.widget_box import HBox
  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
  from sklearn.ensemble import RandomForestRegressor
  from traitlets.traitlets import Dict
  import dalex
  from dalex.model_explanations._variable_importance.loss_functions import *
  from dalex.aspect._predict_aspect_importance.object import PredictAspectImportance
  from dalex.aspect._model_triplot.object import ModelTriplot
  from dalex.aspect._predict_triplot.object import PredictTriplot
  from dalex.aspect._model_aspect_importance.object import ModelAspectImportance
label_desc: Use image node_id 2 for calling the AspectTestFifa obj's underlying member method code with example usage: obj.test() without return types