updated custom_observation_example.py to highlight how we use predictors

and render custom obvsercations

flatland/envs/observations.py

@@ -308,6 +308,7 @@ class TreeObsForRailEnv(ObservationBuilder):
         We walk along the branch and collect the information documented in the get() function.
         If there is a branching point a new node is created and each possible branch is explored.
         """
+
         # [Recursive branch opened]
         if depth >= self.max_depth + 1:
             return [], []

flatland/envs/predictions.py

@@ -86,7 +86,7 @@ class ShortestPathPredictorForRailEnv(PredictionBuilder):
     The prediction acts as if no other agent is in the environment and always takes the forward action.
     """
 
-    def __init__(self, max_depth):
+    def __init__(self, max_depth=20):
         self.max_depth = max_depth
 
     def get(self, custom_args=None, handle=None):

flatland/utils/rendertools.py

@@ -304,10 +304,6 @@ class RenderTool(object):
             warnings.warn(
                 "Predictor did not provide any predicted cells to render. \
                 Predictors builder needs to populate: env.dev_pred_dict")
-
-
-
-
         else:
             for agent in agent_handles:
                 color = self.gl.get_agent_color(agent)