class_docstr: An implementation of `"GeoScattering" <http://proceedings.mlr.press/v97/gao19e.html>`_
  from the ICML '19 paper "Geometric Scattering for Graph Data Analysis". The procedure
  uses scattering with wavelet transforms to create graph spectral descriptors. Moments of the
  wavelet transformed features are used as graph level features for the embedding.
  
  Args:
      order (int): Adjacency matrix powers. Default is 4.
      moments (int): Unnormalized moments considered. Default is 4.
      seed (int): Random seed value. Default is 42.
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docstr: Calculating the wavelets of a normalized self-looped adjacency matrix.
  
  Arg types:
      * **A_hat** *(SciPy array)* - The normalized adjacency matrix.
  
  Return types:
      * **Psi** *(List of Scipy arrays)* - The wavelet matrices.
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code: def _calculate_wavelets(self, A_hat):
      """
      Calculating the wavelets of a normalized self-looped adjacency matrix.
  
      Arg types:
          * **A_hat** *(SciPy array)* - The normalized adjacency matrix.
  
      Return types:
          * **Psi** *(List of Scipy arrays)* - The wavelet matrices.
      """
      Psi = [
          A_hat.power(2**power) - A_hat.power(2 ** (power + 1))
          for power in range(self.order + 1)
      ]
      return Psi
  
imports: import math
  import numpy
  import networkx
  from typing import List
  import scipy.stats.mstats
  import scipy.sparse
  from karateclub.estimator import Estimator
label_desc: Use image node_id 4 for calling the GeoScattering obj's underlying member method code with example usage: obj._calculate_wavelets(A_hat) and returns: Psi