From 2eace8df607bf89e3b9f6099a481c9125d3d21d8 Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Thu, 31 Oct 2019 11:50:35 -0400
Subject: [PATCH] Fixing comment bu mohanty, introducing enum
---
examples/introduction_flatland_2_1.py | 8 +++++---
1 file changed, 5 insertions(+), 3 deletions(-)
diff --git a/examples/introduction_flatland_2_1.py b/examples/introduction_flatland_2_1.py
index 4cdf63b0..cf6b69dc 100644
--- a/examples/introduction_flatland_2_1.py
+++ b/examples/introduction_flatland_2_1.py
@@ -6,6 +6,7 @@ import numpy as np
from flatland.envs.observations import GlobalObsForRailEnv
# First of all we import the Flatland rail environment
from flatland.envs.rail_env import RailEnv
+from flatland.envs.rail_env import RailEnvActions
from flatland.envs.rail_generators import sparse_rail_generator
from flatland.envs.schedule_generators import sparse_schedule_generator
# We also include a renderer because we want to visualize what is going on in the environment
@@ -27,8 +28,8 @@ from flatland.utils.rendertools import RenderTool, AgentRenderVariant
# The railway infrastructure can be build using any of the provided generators in env/rail_generators.py
# Here we use the sparse_rail_generator with the following parameters
-width = 16*7 # With of map
-height = 9*7 # Height of map
+width = 16 * 7 # With of map
+height = 9 * 7 # Height of map
nr_trains = 20 # Number of trains that have an assigned task in the env
cities_in_map = 20 # Number of cities where agents can start or end
seed = 14 # Random seed
@@ -109,7 +110,8 @@ class RandomAgent:
:param state: input is the observation of the agent
:return: returns an action
"""
- return np.random.choice([1, 2, 3, 4]) # [Left, Forward, Right, Stop]
+ return np.random.choice([RailEnvActions.MOVE_FORWARD, RailEnvActions.MOVE_RIGHT, RailEnvActions.MOVE_LEFT,
+ RailEnvActions.STOP_MOVING])
def step(self, memories):
"""
--
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