code: def __init__(self, x_dim, sigma=0.1, rshell=2, center=0):
      self.sigma = sigma
      self.rshell = rshell
      if not hasattr(center, "__len__"):
          self.center = np.array([center] * x_dim)
      elif isinstance(center, list):
          self.center = np.array(center)
      else:
          self.center = center
      super(GaussianShell, self).__init__(x_dim)
  
imports: import copy
  import numpy
  from scipy.stats import multivariate_normal
  import scipy.special
label_desc: Use image node_id 1 to create a new GaussianShell object from inherited base classes: Likelihood with example: obj = GaussianShell(x_dim, sigma, rshell, center)