From dae7c424b94380d78195fafbc50a14f7f5c6165d Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Sat, 31 Aug 2019 19:54:30 -0400
Subject: [PATCH] minor bugfixes
---
examples/flatland_2_0_example.py | 8 ++++----
flatland/envs/rail_generators.py | 15 ++++++++-------
2 files changed, 12 insertions(+), 11 deletions(-)
diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index caa6e80c..a99009a5 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -30,18 +30,18 @@ speed_ration_map = {1.: 0.25, # Fast passenger train
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=30, # Number of cities in map (where train stations are)
+ rail_generator=sparse_rail_generator(num_cities=20, # Number of cities in map (where train stations are)
num_intersections=5, # Number of intersections (no start / target)
- num_trainstations=20, # Number of possible start/targets on map
+ num_trainstations=15, # Number of possible start/targets on map
min_node_dist=3, # Minimal distance of nodes
node_radius=2, # Proximity of stations to city center
- num_neighb=3, # Number of connections to other cities/intersections
+ num_neighb=4, # Number of connections to other cities/intersections
seed=15, # Random seed
realistic_mode=True,
enhance_intersection=True
),
schedule_generator=sparse_schedule_generator(speed_ration_map),
- number_of_agents=40,
+ number_of_agents=10,
stochastic_data=stochastic_data, # Malfunction data generator
obs_builder_object=TreeObservation)
diff --git a/flatland/envs/rail_generators.py b/flatland/envs/rail_generators.py
index 17db869e..d915fdc7 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -573,14 +573,15 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
x_positions = np.linspace(node_radius, height - node_radius, nodes_per_row, dtype=int)
y_positions = np.linspace(node_radius, width - node_radius, nodes_per_col, dtype=int)
- fraction = 0
- city_fraction = num_cities / tot_num_node
- step = np.gcd(num_intersections, num_cities) / tot_num_node
+ fraction = 0
+ city_fraction = num_cities / tot_num_node
+ step = np.gcd(num_intersections, num_cities) / tot_num_node
+
for node_idx in range(num_cities + num_intersections):
to_close = True
tries = 0
- fraction = (fraction + step) % 1.
+
if not realistic_mode:
while to_close:
x_tmp = node_radius + np.random.randint(height - node_radius)
@@ -608,13 +609,13 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
warnings.warn("Could not set nodes, please change initial parameters!!!!")
break
else:
+ fraction = (fraction + step) % 1.
x_tmp = x_positions[node_idx % nodes_per_row]
y_tmp = y_positions[node_idx // nodes_per_row]
if len(city_positions) < num_cities and fraction < city_fraction:
city_positions.append((x_tmp, y_tmp))
else:
intersection_positions.append((x_tmp, y_tmp))
- print(len(city_positions))
node_positions = city_positions + intersection_positions
# Chose node connection
@@ -634,13 +635,13 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
available_nodes_full = np.delete(available_nodes_full, delete_idx, 0)
# Priority city to intersection connections
- if current_node < num_cities and len(available_intersections) > 0:
+ if False and current_node < num_cities and len(available_intersections) > 0:
available_nodes = available_intersections
delete_idx = np.where(available_cities == current_node)
available_cities = np.delete(available_cities, delete_idx, 0)
# Priority intersection to city connections
- elif current_node >= num_cities and len(available_cities) > 0:
+ elif False and current_node >= num_cities and len(available_cities) > 0:
available_nodes = available_cities
delete_idx = np.where(available_intersections == current_node)
available_intersections = np.delete(available_intersections, delete_idx, 0)
--
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