From 34fa9914d4e8a173a4cf417156467d4a5b77c4d4 Mon Sep 17 00:00:00 2001
From: Dipam Chakraborty <dipam@aicrowd.com>
Date: Wed, 8 Sep 2021 22:44:03 +0530
Subject: [PATCH] fix multi speed init test
---
tests/test_multi_speed.py | 11 ++++++++---
1 file changed, 8 insertions(+), 3 deletions(-)
diff --git a/tests/test_multi_speed.py b/tests/test_multi_speed.py
index 5918c24e..561057d8 100644
--- a/tests/test_multi_speed.py
+++ b/tests/test_multi_speed.py
@@ -8,6 +8,7 @@ from flatland.envs.rail_generators import sparse_rail_generator, rail_from_grid_
from flatland.envs.line_generators import sparse_line_generator
from flatland.utils.simple_rail import make_simple_rail
from test_utils import ReplayConfig, Replay, run_replay_config, set_penalties_for_replay
+from flatland.envs.agent_utils import RailAgentStatus
# Use the sparse_rail_generator to generate feasible network configurations with corresponding tasks
@@ -49,7 +50,7 @@ class RandomAgent:
def test_multi_speed_init():
env = RailEnv(width=50, height=50,
rail_generator=sparse_rail_generator(seed=2), line_generator=sparse_line_generator(),
- random_seed=2,
+ random_seed=3,
number_of_agents=3)
# Initialize the agent with the parameters corresponding to the environment and observation_builder
@@ -62,13 +63,17 @@ def test_multi_speed_init():
# Reset environment and get initial observations for all agents
env.reset(False, False)
+ for a_idx in range(len(env.agents)):
+ env.agents[a_idx].position = env.agents[a_idx].initial_position
+ env.agents[a_idx].status = RailAgentStatus.ACTIVE
+
# Here you can also further enhance the provided observation by means of normalization
# See training navigation example in the baseline repository
old_pos = []
for i_agent in range(env.get_num_agents()):
- env.agents[i_agent].speed_data['speed'] = 1. / (i_agent + 2)
+ env.agents[i_agent].speed_data['speed'] = 1. / (i_agent + 1)
old_pos.append(env.agents[i_agent].position)
-
+ print(env.agents[i_agent].position)
# Run episode
for step in range(100):
--
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