diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 898f6a9906e998e70ac41f0833e57a4df2fbcac1..ca9346fc71a8d5485d7b71098dc91558d09bd929 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -32,16 +32,16 @@ speed_ration_map = {1.: 0.25, # Fast passenger train
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=5, # Number of cities in map (where train stations are)
- num_intersections=4, # Number of intersections (no start / target)
+ rail_generator=sparse_rail_generator(num_cities=9, # Number of cities in map (where train stations are)
num_trainstations=100, # Number of possible start/targets on map
min_node_dist=10, # Minimal distance of nodes
node_radius=4, # Proximity of stations to city center
num_neighb=2, # Number of connections to other cities/intersections
seed=15, # Random seed
grid_mode=True,
- nr_inter_connections=2,
- max_nr_connection_points=12
+ nr_parallel_tracks=2,
+ connectin_points_per_side=3,
+ max_nr_connection_directions=2,
),
schedule_generator=sparse_schedule_generator(),
number_of_agents=50,
diff --git a/flatland/envs/rail_generators.py b/flatland/envs/rail_generators.py
index 147b1bd14a5943f87f4d78f37e9ea7e1722c9087..117862a71593f8483928323574d8977898cfdc9c 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -528,8 +528,9 @@ def random_rail_generator(cell_type_relative_proportion=[1.0] * 11) -> RailGener
return generator
-def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2, min_node_dist=20, node_radius=2,
- num_neighb=3, nr_inter_connections=2, grid_mode=False, max_nr_connection_points=4,
+def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, node_radius=2,
+ num_neighb=3, nr_parallel_tracks=2, grid_mode=False, connectin_points_per_side=4,
+ max_nr_connection_directions=2,
seed=0) -> RailGenerator:
"""
This is a level generator which generates complex sparse rail configurations
@@ -566,7 +567,7 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
# Evenly distribute cities and intersections
node_positions: List[Any] = None
- nb_nodes = num_cities + num_intersections
+ nb_nodes = num_cities
if grid_mode:
nodes_ratio = height / width
nodes_per_row = int(np.ceil(np.sqrt(nb_nodes * nodes_ratio)))
@@ -591,14 +592,14 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
# reduce nb_nodes, _num_cities, _num_intersections if less were generated in not_grid_mode
nb_nodes = len(node_positions)
_num_cities = len(city_positions)
- _num_intersections = len(intersection_positions)
# Chose node connection
# Set up list of available nodes to connect to
available_nodes = np.arange(nb_nodes)
# Set up connection points for all cities
- connection_points = _generate_node_connection_points(node_positions, node_radius, max_nr_connection_points)
+ connection_points = _generate_node_connection_points(node_positions, node_radius, connectin_points_per_side,
+ max_nr_connection_directions)
# Start at some node
current_node = np.random.randint(len(available_nodes))
@@ -639,8 +640,8 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
tmp_dist_to_node = distance_on_rail(tmp_out_connection_point, node_positions[neighb])
connection_distances.append(tmp_dist_to_node)
possible_connection_points = argsort(connection_distances)
- for sort_idx in possible_connection_points[:nr_inter_connections]:
- # Find closes connection point
+ for sort_idx in possible_connection_points[:nr_parallel_tracks]:
+ # Find closest connection point
tmp_out_connection_point = connection_points[current_node][sort_idx]
min_connection_dist = np.inf
for tmp_in_connection_point in connection_points[neighb]:
@@ -705,7 +706,6 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
connection_points[trainstation_node][corner_node_idx],
(station_x, station_y))
if len(connection) != 0:
-
if (connection_points[trainstation_node][corner_node_idx],
trainstation_node) in boarder_connections:
boarder_connections.remove(
@@ -748,6 +748,7 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
for tbd in to_be_deleted:
boarder_connections.remove(tbd)
print(boarder_connections)
+
# Fix all nodes with illegal transition maps
empty_to_fix = []
rails_to_fix = []
@@ -866,24 +867,28 @@ def sparse_rail_generator(num_cities=5, num_intersections=4, num_trainstations=2
node_positions = city_positions + intersection_positions
return node_positions
- def _generate_node_connection_points(node_positions, node_size, max_nr_connection_points=2):
+ def _generate_node_connection_points(node_positions, node_size, max_nr_connection_points=2,
+ max_nr_connection_directions=2):
connection_points = []
for node_position in node_positions:
- n_connection_points = max_nr_connection_points # np.random.randint(1, max_nr_connection_points)
- connection_per_direction = n_connection_points // 4
- connection_point_vector = [connection_per_direction, connection_per_direction, connection_per_direction,
- n_connection_points - 3 * connection_per_direction]
+ connection_sides_idx = np.sort(
+ np.random.choice(np.arange(4), size=max_nr_connection_directions, replace=False))
+ connections_per_direction = np.zeros(4, dtype=int)
+
+ # set the number of connection points for each direction
+ for idx in connection_sides_idx:
+ connections_per_direction[idx] = max_nr_connection_points
connection_points_coordinates = []
random_connection_slots = False
for direction in range(4):
if random_connection_slots:
connection_slots = np.random.choice(np.arange(-node_size, node_size),
- size=connection_point_vector[direction],
+ size=connections_per_direction[direction],
replace=False)
else:
- connection_slots = np.arange(connection_point_vector[direction]) - int(
- connection_point_vector[direction] / 2)
- for connection_idx in range(connection_point_vector[direction]):
+ connection_slots = np.arange(connections_per_direction[direction]) - int(
+ connections_per_direction[direction] / 2)
+ for connection_idx in range(connections_per_direction[direction]):
if direction == 0:
connection_points_coordinates.append(
(node_position[0] - node_size, node_position[1] + connection_slots[connection_idx]))