diff --git a/examples/Simple_Realistic_Railway_Generator.py b/examples/Simple_Realistic_Railway_Generator.py
index 97444eccc164884ff7720203197140d9f1a8c401..6e5e6a566b7f2e462d310969be8585efec431970 100644
--- a/examples/Simple_Realistic_Railway_Generator.py
+++ b/examples/Simple_Realistic_Railway_Generator.py
@@ -230,13 +230,13 @@ def realistic_rail_generator(num_cities=5,
org_s_nodes: IntVector2DArrayType,
org_e_nodes: IntVector2DArrayType,
nodes_added: IntVector2DArrayType,
- inter_connect_max_nbr_of_shortes_city: int):
+ intern_connect_max_nbr_of_shortes_city: int):
city_edges = []
s_nodes = copy.deepcopy(org_s_nodes)
e_nodes = copy.deepcopy(org_e_nodes)
- for k in range(inter_connect_max_nbr_of_shortes_city):
+ for nbr_connected in range(intern_connect_max_nbr_of_shortes_city):
for city_loop in range(len(s_nodes)):
sns = s_nodes[city_loop]
for start_node in sns:
@@ -278,13 +278,14 @@ def realistic_rail_generator(num_cities=5,
grid_map.grid[start_node] = tmp_trans_sn
grid_map.grid[end_node] = tmp_trans_en
+
connect_sub_graphs(rail_trans, grid_map, org_s_nodes, org_e_nodes, city_edges, nodes_added)
def connect_random_stations(rail_trans: RailEnvTransitions, grid_map: GridTransitionMap,
start_nodes_added: IntVector2DArrayType,
end_nodes_added: IntVector2DArrayType,
nodes_added: IntVector2DArrayType,
- inter_connect_max_nbr_of_shortes_city: int):
+ intern_connect_max_nbr_of_shortes_city: int):
x = np.arange(len(start_nodes_added))
random_city_idx = np.random.choice(x, len(x), False)
@@ -298,14 +299,10 @@ def realistic_rail_generator(num_cities=5,
e_nodes = end_nodes_added[idx_b]
max_input_output = max(len(s_nodes), len(e_nodes))
- max_input_output = min(inter_connect_max_nbr_of_shortes_city, max_input_output)
+ max_input_output = min(intern_connect_max_nbr_of_shortes_city, max_input_output)
- if do_random_connect_stations:
- idx_s_nodes = np.random.choice(np.arange(len(s_nodes)), len(s_nodes), False)
- idx_e_nodes = np.random.choice(np.arange(len(e_nodes)), len(e_nodes), False)
- else:
- idx_s_nodes = np.arange(len(s_nodes))
- idx_e_nodes = np.arange(len(e_nodes))
+ idx_s_nodes = np.random.choice(np.arange(len(s_nodes)), len(s_nodes), False)
+ idx_e_nodes = np.random.choice(np.arange(len(e_nodes)), len(e_nodes), False)
if len(idx_s_nodes) < max_input_output:
idx_s_nodes = np.append(idx_s_nodes, np.random.choice(np.arange(len(s_nodes)), max_input_output - len(
@@ -315,10 +312,10 @@ def realistic_rail_generator(num_cities=5,
np.random.choice(np.arange(len(idx_e_nodes)), max_input_output - len(
idx_e_nodes)))
- if len(idx_s_nodes) > inter_connect_max_nbr_of_shortes_city:
- idx_s_nodes = np.random.choice(idx_s_nodes, inter_connect_max_nbr_of_shortes_city, False)
- if len(idx_e_nodes) > inter_connect_max_nbr_of_shortes_city:
- idx_e_nodes = np.random.choice(idx_e_nodes, inter_connect_max_nbr_of_shortes_city, False)
+ if len(idx_s_nodes) > intern_connect_max_nbr_of_shortes_city:
+ idx_s_nodes = np.random.choice(idx_s_nodes, intern_connect_max_nbr_of_shortes_city, False)
+ if len(idx_e_nodes) > intern_connect_max_nbr_of_shortes_city:
+ idx_e_nodes = np.random.choice(idx_e_nodes, intern_connect_max_nbr_of_shortes_city, False)
for i in range(max_input_output):
start_node = s_nodes[idx_s_nodes[i]]
@@ -360,12 +357,12 @@ def realistic_rail_generator(num_cities=5,
if print_out_info:
print("intern_nbr_of_switches_per_station_track:", intern_nbr_of_switches_per_station_track)
- inter_connect_max_nbr_of_shortes_city = connect_max_nbr_of_shortes_city
+ intern_connect_max_nbr_of_shortes_city = connect_max_nbr_of_shortes_city
if connect_max_nbr_of_shortes_city < 1:
- warnings.warn("min inter_connect_max_nbr_of_shortes_city requried to be > 1!")
- inter_connect_max_nbr_of_shortes_city = 1
+ warnings.warn("min intern_connect_max_nbr_of_shortes_city requried to be > 1!")
+ intern_connect_max_nbr_of_shortes_city = 1
if print_out_info:
- print("inter_connect_max_nbr_of_shortes_city:", inter_connect_max_nbr_of_shortes_city)
+ print("intern_connect_max_nbr_of_shortes_city:", intern_connect_max_nbr_of_shortes_city)
agent_start_targets_nodes = []
@@ -395,10 +392,10 @@ def realistic_rail_generator(num_cities=5,
if True:
if do_random_connect_stations:
connect_random_stations(rail_trans, grid_map, s_nodes, e_nodes, nodes_added,
- inter_connect_max_nbr_of_shortes_city)
+ intern_connect_max_nbr_of_shortes_city)
else:
connect_stations(rail_trans, grid_map, s_nodes, e_nodes, nodes_added,
- inter_connect_max_nbr_of_shortes_city)
+ intern_connect_max_nbr_of_shortes_city)
# ----------------------------------------------------------------------------------
# fix all transition at starting / ending points (mostly add a dead end, if missing)
@@ -459,13 +456,13 @@ if os.path.exists("./../render_output/"):
height=40 + np.random.choice(100),
rail_generator=realistic_rail_generator(num_cities=2 + np.random.choice(10),
city_size=10 + np.random.choice(10),
- allowed_rotation_angles=np.arange(-180, 180, 15),
+ allowed_rotation_angles=[0],
max_number_of_station_tracks=np.random.choice(4) + 4,
nbr_of_switches_per_station_track=np.random.choice(4) + 2,
connect_max_nbr_of_shortes_city=2,
- do_random_connect_stations=np.random.choice(1) == 0,
+ do_random_connect_stations=False,
# Number of cities in map
- seed=int(time.time()), # Random seed
+ seed=0*int(time.time()), # Random seed
print_out_info=True
),
schedule_generator=sparse_schedule_generator(),
diff --git a/flatland/core/grid/grid4_astar.py b/flatland/core/grid/grid4_astar.py
index 5bec1ce454df9e6c41ad8c48fae243116f4ff222..c04d71dd57c8ea90d3beb592c4c83329d22e7b80 100644
--- a/flatland/core/grid/grid4_astar.py
+++ b/flatland/core/grid/grid4_astar.py
@@ -9,14 +9,14 @@ from flatland.core.transition_map import GridTransitionMap
class AStarNode:
"""A node class for A* Pathfinding"""
- def __init__(self, parent=None, pos=None):
- self.parent = parent
- self.pos = pos
- self.g = 0
- self.h = 0
- self.f = 0
-
- def __eq__(self, other):
+ def __init__(self, parent: IntVector2D = None, pos: IntVector2D = None):
+ self.parent: IntVector2D = parent
+ self.pos: IntVector2D = pos
+ self.g: float = 0.0
+ self.h: float = 0.0
+ self.f: float = 0.0
+
+ def __eq__(self, other: IntVector2D):
return self.pos == other.pos
def __hash__(self):
@@ -95,7 +95,7 @@ def a_star(rail_trans: RailEnvTransitions,
continue
# create the f, g, and h values
- child.g = current_node.g + 1
+ child.g = current_node.g + 1.0
# this heuristic avoids diagonal paths
child.h = Vec2d.get_manhattan_distance(child.pos, end_node.pos)
child.f = child.g + child.h