From 96f38175bfc927352d50ce5b6fdb025be0f5c43a Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Sat, 31 Aug 2019 14:35:38 -0400
Subject: [PATCH] updated example of Flatland 2.0 and minor changes to schedule
generator
---
examples/flatland_2_0_example.py | 24 +++++++++++++-----------
flatland/envs/schedule_generators.py | 5 ++++-
2 files changed, 17 insertions(+), 12 deletions(-)
diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 71a185c7..6f6c4b08 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -1,9 +1,9 @@
import numpy as np
-from flatland.envs.rail_generators import sparse_rail_generator
from flatland.envs.observations import TreeObsForRailEnv
from flatland.envs.predictions import ShortestPathPredictorForRailEnv
from flatland.envs.rail_env import RailEnv
+from flatland.envs.rail_generators import sparse_rail_generator
from flatland.envs.schedule_generators import sparse_schedule_generator
from flatland.utils.rendertools import RenderTool
@@ -13,17 +13,23 @@ np.random.seed(1)
# Training on simple small tasks is the best way to get familiar with the environment
# Use a the malfunction generator to break agents from time to time
-stochastic_data = {'prop_malfunction': 0.5, # Percentage of defective agents
+stochastic_data = {'prop_malfunction': 0.0, # Percentage of defective agents
'malfunction_rate': 30, # Rate of malfunction occurence
'min_duration': 3, # Minimal duration of malfunction
'max_duration': 10 # Max duration of malfunction
}
TreeObservation = TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv())
-env = RailEnv(width=20,
- height=20,
- rail_generator=sparse_rail_generator(num_cities=2, # Number of cities in map (where train stations are)
- num_intersections=1, # Number of intersections (no start / target)
+
+speed_ration_map = {1.: 0.1, # Fast passenger train
+ 0.5: 0.2, # Slow commuter train
+ 0.25: 0.2, # Fast freight train
+ 0.125: 0.5} # Slow freight train
+
+env = RailEnv(width=50,
+ height=50,
+ rail_generator=sparse_rail_generator(num_cities=10, # Number of cities in map (where train stations are)
+ num_intersections=5, # Number of intersections (no start / target)
num_trainstations=15, # Number of possible start/targets on map
min_node_dist=3, # Minimal distance of nodes
node_radius=3, # Proximity of stations to city center
@@ -32,7 +38,7 @@ env = RailEnv(width=20,
realistic_mode=True,
enhance_intersection=True
),
- schedule_generator=sparse_schedule_generator(),
+ schedule_generator=sparse_schedule_generator(speed_ration_map),
number_of_agents=5,
stochastic_data=stochastic_data, # Malfunction data generator
obs_builder_object=TreeObservation)
@@ -83,10 +89,6 @@ action_dict = dict()
print("Start episode...")
# Reset environment and get initial observations for all agents
obs = env.reset()
-# Update/Set agent's speed
-for idx in range(env.get_num_agents()):
- speed = 1.0 / ((idx % 5) + 1.0)
- env.agents[idx].speed_data["speed"] = speed
# Reset the rendering sytem
env_renderer.reset()
diff --git a/flatland/envs/schedule_generators.py b/flatland/envs/schedule_generators.py
index 4843e004..a0f6825d 100644
--- a/flatland/envs/schedule_generators.py
+++ b/flatland/envs/schedule_generators.py
@@ -60,7 +60,10 @@ def sparse_schedule_generator(speed_ratio_map: Mapping[float, float] = None) ->
def generator(rail: GridTransitionMap, num_agents: int, hints: Any = None):
train_stations = hints['train_stations']
agent_start_targets_nodes = hints['agent_start_targets_nodes']
- num_agents = hints['num_agents']
+ max_num_agents = hints['num_agents']
+ if num_agents > max_num_agents:
+ num_agents = max_num_agents
+ warnings.warn("Too many agents! Changes number of agents.")
# Place agents and targets within available train stations
agents_position = []
agents_target = []
--
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