class_docstr: Implementation of the visual foraging environment used for scene construction simulations 
class_docstr_tok: ["Implementation","of","the","visual","foraging","environment","used","for","scene","construction","simulations"]
code: def step(self, actions):
      prob_states = np.empty(self.n_factors, dtype=object)
      for f in range(self.n_factors):
          prob_states[f] = (
              self._transition_dist[f][:, :, actions[f]]
              .dot(self._state[f], return_numpy=True)
              .flatten()
          )
      state = Categorical(values=prob_states).sample()
      self._state = self._construct_state(state)
      return self._get_observation()
  
imports: from pymdp.envs import Env
  from pymdp import utils, maths
  import numpy
  from itertools import permutations, product
label_desc: Use image node_id 3 for calling the VisualForagingEnv obj's underlying member method code with example usage: obj.step(actions) and returns: self