code: def extract_feature_(self, persistence_diagram):
      # As practice shows, only 1st layer of 1st homology dimension plays role
      persistence_landscape = PersistenceLandscape(
          n_jobs=1
      ).fit_transform([persistence_diagram])[0, 1, 0, :]
      return np.array(
          [
              np.sum(persistence_landscape)
              / persistence_landscape.shape[0]
          ]
      )
  
imports: from abc import ABC
  import numpy
  import pandas
  from gtda.diagrams import Scaler, Filtering, PersistenceEntropy, PersistenceLandscape, BettiCurve
  from gtda.homology import VietorisRipsPersistence
label_desc: Use image node_id 2 for calling the AveragePersistenceLandscapeFeature obj's underlying member method code with example usage: obj.extract_feature_(persistence_diagram) and returns: np