class_docstr: 2-dimensional grid-world implementation with 5 actions (the 4 cardinal directions and staying put).
code: def get_likelihood_dist(self):
      A = np.eye(self.n_observations, self.n_states)
      return A
  
imports: import numpy
  import matplotlib.pyplot
  import seaborn
  from pymdp.envs import Env
label_desc: Use image node_id 10 for calling the GridWorldEnv obj's underlying member method code with example usage: obj.get_likelihood_dist() and returns: A