From 1a91a7383d8b7358b2ef0d080d7f62ca9a51af13 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Fri, 14 Jun 2019 00:04:06 +0200
Subject: [PATCH] Minor bugfixes in shortes path predictor
---
examples/training_example.py | 2 +-
flatland/envs/observations.py | 1 -
flatland/envs/predictions.py | 15 ++++++++-------
3 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/examples/training_example.py b/examples/training_example.py
index 78336b9..218f133 100644
--- a/examples/training_example.py
+++ b/examples/training_example.py
@@ -80,7 +80,7 @@ for trials in range(1, n_trials + 1):
# Environment step which returns the observations for all agents, their corresponding
# reward and whether their are done
next_obs, all_rewards, done, _ = env.step(action_dict)
- TreeObservation.util_print_obs_subtree(next_obs[0], num_features_per_node=8)
+ # TreeObservation.util_print_obs_subtree(next_obs[0], num_features_per_node=8)
# Update replay buffer and train agent
for a in range(env.get_num_agents()):
agent.step((obs[a], action_dict[a], all_rewards[a], next_obs[a], done[a]))
diff --git a/flatland/envs/observations.py b/flatland/envs/observations.py
index 885a966..b5d9c2e 100644
--- a/flatland/envs/observations.py
+++ b/flatland/envs/observations.py
@@ -178,7 +178,6 @@ class TreeObsForRailEnv(ObservationBuilder):
self.predicted_pos = {}
self.predicted_dir = {}
self.predictions = self.predictor.get(self.distance_map)
-
for t in range(len(self.predictions[0])):
pos_list = []
dir_list = []
diff --git a/flatland/envs/predictions.py b/flatland/envs/predictions.py
index 988594e..366acfe 100644
--- a/flatland/envs/predictions.py
+++ b/flatland/envs/predictions.py
@@ -127,14 +127,15 @@ class ShortestPathPredictorForRailEnv(PredictionBuilder):
if np.sum(cell_transitions) == 1:
new_direction = np.argmax(cell_transitions)
new_position = self._new_position(agent.position, new_direction)
- else:
+ elif np.sum(cell_transitions) > 1:
+ min_dist = np.inf
for direct in range(4):
- min_dist = np.inf
- target_dist = distancemap[agent_idx, agent.position[0], agent.position[1], direct]
- if target_dist < min_dist:
- min_dist = target_dist
- new_direction = direct
- new_position = self._new_position(agent.position, new_direction)
+ if cell_transitions[direct] == 1:
+ target_dist = distancemap[agent_idx, agent.position[0], agent.position[1], direct]
+ if target_dist < min_dist:
+ min_dist = target_dist
+ new_direction = direct
+ new_position = self._new_position(agent.position, new_direction)
agent.position = new_position
agent.direction = new_direction
--
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