class_docstr: Implementation of the 3-arm T-Maze environment where there is an additional null outcome within the cue modality, so that the agent
  doesn't get a random cue observation, but a null one, when it visits non-cue locations
class_docstr_tok: ["Implementation","of","the","3-arm","T-Maze","environment","where","there","is","an","additional","null","outcome","within","the","cue","modality",",","so","that","the","agent","does","n't","get","a","random","cue","observation",",","but","a","null","one",",","when","it","visits","non-cue","locations"]
code: def reward_condition(self):
      return self._reward_condition
  
imports: from pymdp.envs import Env
  from pymdp import utils, maths
  import numpy
label_desc: Use image node_id 12 for calling the TMazeEnvNullOutcome obj's underlying member method code with example usage: obj.reward_condition() and returns: self