diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 2fa48e9622529c52034d57079e4a1dc429cf564d..f2bb4aba099eda538cf6a1ed408cd1eb7cb04548 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -32,14 +32,14 @@ speed_ration_map = {1.: 0.25, # Fast passenger train
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=11, # Number of cities in map (where train stations are)
- num_trainstations=50, # Number of possible start/targets on map
+ rail_generator=sparse_rail_generator(num_cities=9, # Number of cities in map (where train stations are)
+ num_trainstations=0, # Number of possible start/targets on map
min_node_dist=8, # Minimal distance of nodes
node_radius=3, # Proximity of stations to city center
seed=15, # Random seed
- grid_mode=False,
+ grid_mode=True,
max_connection_points_per_side=2,
- max_nr_connection_directions=2,
+ max_nr_connection_directions=4
),
schedule_generator=sparse_schedule_generator(),
number_of_agents=50,
diff --git a/flatland/core/grid/grid_utils.py b/flatland/core/grid/grid_utils.py
index 1dc625c9f0166cedb16696e8ef34e8e097ba7902..14015d1a062c91c134320c80e390577d49bad72a 100644
--- a/flatland/core/grid/grid_utils.py
+++ b/flatland/core/grid/grid_utils.py
@@ -293,7 +293,7 @@ def distance_on_rail(pos1, pos2):
return np.sqrt(np.power(pos1[0] - pos2[0], 2) + np.power(pos1[1] - pos2[1], 2))
-def closest_direction(pos1, pos2):
+def direction_to_point(pos1, pos2):
"""
Returns the closest direction orientation of position 2 relative to position 1
:param pos1: position we are interested in
@@ -305,9 +305,9 @@ def closest_direction(pos1, pos2):
direction = np.sign(diff_vec[axis])
if axis == 0:
if direction > 0:
- return 2
- else:
return 0
+ else:
+ return 2
else:
if direction > 0:
return 3
diff --git a/flatland/envs/rail_generators.py b/flatland/envs/rail_generators.py
index e06e956a3d9857fbcc5dbd936c601ef7d40d506d..8c66fe39460dfdb05150e53979edca548377c6b4 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -6,7 +6,7 @@ import msgpack
import numpy as np
from flatland.core.grid.grid4_utils import get_direction, mirror
-from flatland.core.grid.grid_utils import distance_on_rail, closest_direction
+from flatland.core.grid.grid_utils import distance_on_rail, direction_to_point
from flatland.core.grid.rail_env_grid import RailEnvTransitions
from flatland.core.transition_map import GridTransitionMap
from flatland.envs.grid4_generators_utils import connect_rail, connect_nodes
@@ -701,7 +701,8 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
# TODO: Change the way this code works! Check that we get sufficient direction.
# TODO: Check if this works as expected
while len(connection_sides_idx) < max_nr_connection_directions and idx < len(neighb_dist):
- current_closest_direction = closest_direction(node_position, node_positions[closest_neighb_idx[idx]])
+ current_closest_direction = direction_to_point(node_position, node_positions[closest_neighb_idx[idx]])
+ print(node_position)
if current_closest_direction not in connection_sides_idx:
connection_sides_idx.append(current_closest_direction)
idx += 1
@@ -711,7 +712,7 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
connections_per_direction = np.zeros(4, dtype=int)
for idx in connection_sides_idx:
- nr_of_connection_points = np.random.randint(1, max_nr_connection_points + 1)
+ nr_of_connection_points = max_nr_connection_points # np.random.randint(1, max_nr_connection_points + 1)
connections_per_direction[idx] = nr_of_connection_points
connection_points_coordinates = []
@@ -722,13 +723,13 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
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]))
+ (node_position[0] - node_size, node_position[1] + connection_slots[connection_idx]))
if direction == 1:
connection_points_coordinates.append(
(node_position[0] + connection_slots[connection_idx], node_position[1] + node_size))
if direction == 2:
connection_points_coordinates.append(
- (node_position[0] - node_size, node_position[1] + connection_slots[connection_idx]))
+ (node_position[0] + node_size, node_position[1] + connection_slots[connection_idx]))
if direction == 3:
connection_points_coordinates.append(
(node_position[0] + connection_slots[connection_idx], node_position[1] - node_size))
@@ -737,8 +738,7 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
connection_info.append(connections_per_direction)
return connection_points, connection_info
- def _connect_cities(node_positions, connection_points, connection_info, rail_trans,
- grid_map):
+ def _connect_cities(node_positions, connection_points, connection_info, rail_trans, grid_map):
"""
Function to connect the different cities through their connection points
:param node_positions: Positions of city centers
@@ -755,7 +755,7 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
if nbr_connection_points > 0:
neighb_idx = _closest_neigh_in_direction(current_node, direction, node_positions)
print(current_node, node_positions[current_node], direction, neighb_idx,
- connection_info[current_node])
+ connection_info[current_node], connection_points[current_node])
else:
direction += 1
continue
@@ -914,17 +914,17 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
def _closest_neigh_in_direction(current_node, direction, node_positions):
# Sort available neighbors according to their distance.
- available_nodes = np.arange(len(node_positions))
+
node_dist = []
- for av_node in available_nodes:
+ for av_node in range(len(node_positions)):
node_dist.append(distance_on_rail(node_positions[current_node], node_positions[av_node]))
- sorted_neighbours = available_nodes[np.argsort(node_dist)]
+ sorted_neighbours = np.argsort(node_dist)
for neighb in sorted_neighbours[1:]:
distance_0 = np.abs(node_positions[current_node][0] - node_positions[neighb][0])
distance_1 = np.abs(node_positions[current_node][1] - node_positions[neighb][1])
if direction == 0:
- if node_positions[neighb][0] > node_positions[current_node][0] and distance_1 <= distance_0:
+ if node_positions[neighb][0] < node_positions[current_node][0] and distance_1 <= distance_0:
return neighb
if direction == 1:
@@ -932,7 +932,7 @@ def sparse_rail_generator(num_cities=5, num_trainstations=2, min_node_dist=20, n
return neighb
if direction == 2:
- if node_positions[neighb][0] < node_positions[current_node][0] and distance_1 <= distance_0:
+ if node_positions[neighb][0] > node_positions[current_node][0] and distance_1 <= distance_0:
return neighb
if direction == 3: