From 4570db2d89ef887c353c70162c9ef5553ac8df69 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Sat, 31 Aug 2019 19:24:57 -0400
Subject: [PATCH] dixing level generator city distribution
---
examples/flatland_2_0_example.py | 10 +++++-----
flatland/envs/rail_generators.py | 12 +++++++++---
2 files changed, 14 insertions(+), 8 deletions(-)
diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 082308e6..caa6e80c 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=10, # Number of cities in map (where train stations are)
- num_intersections=15, # Number of intersections (no start / target)
- num_trainstations=50, # Number of possible start/targets on map
+ rail_generator=sparse_rail_generator(num_cities=30, # 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
min_node_dist=3, # Minimal distance of nodes
- node_radius=3, # Proximity of stations to city center
+ node_radius=2, # Proximity of stations to city center
num_neighb=3, # 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=20,
+ number_of_agents=40,
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 40ec2e0d..17db869e 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -573,9 +573,14 @@ 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
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)
@@ -587,7 +592,7 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
if distance_on_rail((x_tmp, y_tmp), node_pos) < min_node_dist:
to_close = True
- # CHeck distance to intersections
+ # Check distance to intersections
for node_pos in intersection_positions:
if distance_on_rail((x_tmp, y_tmp), node_pos) < min_node_dist:
to_close = True
@@ -605,11 +610,11 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
else:
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 (node_idx % (tot_num_node // num_cities)) == 0:
+ 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
@@ -627,6 +632,7 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
current_node = node_stack[0]
delete_idx = np.where(available_nodes_full == current_node)
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:
available_nodes = available_intersections
--
GitLab