From 1169fcb628da3875ac432efe7495393579f583f4 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Mon, 13 May 2019 17:26:08 +0200
Subject: [PATCH] fixed formatting
---
examples/training_navigation.py | 6 ++++--
flatland/core/env_observation_builder.py | 3 +--
flatland/envs/generators.py | 2 +-
flatland/envs/rail_env.py | 2 +-
4 files changed, 7 insertions(+), 6 deletions(-)
diff --git a/examples/training_navigation.py b/examples/training_navigation.py
index feb4796..ee360a1 100644
--- a/examples/training_navigation.py
+++ b/examples/training_navigation.py
@@ -115,6 +115,7 @@ for trials in range(1, n_trials + 1):
# Reset environment
obs = env.reset()
final_obs = obs.copy()
+ final_obs_next = obs.copy()
for a in range(env.get_num_agents()):
data, distance = env.obs_builder.split_tree(tree=np.array(obs[a]), num_features_per_node=5, current_depth=0)
data = norm_obs_clip(data)
@@ -150,7 +151,8 @@ for trials in range(1, n_trials + 1):
# Update replay buffer and train agent
for a in range(env.get_num_agents()):
if done[a]:
- final_obs[a] = obs[a]
+ final_obs[a] = obs[a].copy()
+ final_obs_next[a] = next_obs[a].copy()
final_action_dict.update({a: action_dict[a]})
if not demo and not done[a]:
agent.step(obs[a], action_dict[a], all_rewards[a], next_obs[a], done[a])
@@ -159,7 +161,7 @@ for trials in range(1, n_trials + 1):
obs = next_obs.copy()
if done['__all__']:
env_done = 1
- agent.step(final_obs[a], final_action_dict[a], all_rewards[a], next_obs[a], done[a])
+ agent.step(final_obs[a], final_action_dict[a], all_rewards[a], final_obs_next[a], done[a])
break
# Epsilon decay
eps = max(eps_end, eps_decay * eps) # decrease epsilon
diff --git a/flatland/core/env_observation_builder.py b/flatland/core/env_observation_builder.py
index 547f349..8e7f2ae 100644
--- a/flatland/core/env_observation_builder.py
+++ b/flatland/core/env_observation_builder.py
@@ -139,8 +139,7 @@ class TreeObsForRailEnv(ObservationBuilder):
for neigh_direction in possible_directions:
new_cell = self._new_position(position, neigh_direction)
- if new_cell[0] >= 0 and new_cell[0] < self.env.height and \
- new_cell[1] >= 0 and new_cell[1] < self.env.width:
+ if new_cell[0] >= 0 and new_cell[0] < self.env.height and new_cell[1] >= 0 and new_cell[1] < self.env.width:
desired_movement_from_new_cell = (neigh_direction + 2) % 4
diff --git a/flatland/envs/generators.py b/flatland/envs/generators.py
index 35af894..e9e2d3d 100644
--- a/flatland/envs/generators.py
+++ b/flatland/envs/generators.py
@@ -143,7 +143,7 @@ def complex_rail_generator(nr_start_goal=1, nr_extra=10, min_dist=2, max_dist=99
if len(new_path) >= 2:
nr_created += 1
- #print("\n> Complex Rail Gen: Created #", len(start_goal), "pairs and #", nr_created, "extra connections")
+ # print("\n> Complex Rail Gen: Created #", len(start_goal), "pairs and #", nr_created, "extra connections")
# print(start_goal)
agents_position = [sg[0] for sg in start_goal]
diff --git a/flatland/envs/rail_env.py b/flatland/envs/rail_env.py
index 40e4ab7..33b9f96 100644
--- a/flatland/envs/rail_env.py
+++ b/flatland/envs/rail_env.py
@@ -300,7 +300,7 @@ class RailEnv(Environment):
# if num_agents_in_target_position == self.number_of_agents:
if np.all([np.array_equal(agent2.position, agent2.target) for agent2 in self.agents]):
self.dones["__all__"] = True
- self.rewards_dict = [r + global_reward for r in self.rewards_dict]
+ self.rewards_dict = [0*r+global_reward for r in self.rewards_dict]
# Reset the step actions (in case some agent doesn't 'register_action'
# on the next step)
--
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