diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py
index 40b415915305df0384b31ad30037ec14ec0e985d..4e97ff11c71f3a9061696c4a5321c45abf02b821 100644
--- a/examples/flatland_2_0_example.py
+++ b/examples/flatland_2_0_example.py
@@ -30,11 +30,11 @@ speed_ration_map = {1.: 0.25, # Fast passenger train
env = RailEnv(width=40,
height=40,
- rail_generator=sparse_rail_generator(num_cities=8, # Number of cities in map (where train stations are)
+ rail_generator=sparse_rail_generator(max_num_cities=8, # Number of cities in map (where train stations are)
seed=1, # Random seed
grid_mode=False,
- max_inter_city_rails=2,
- max_tracks_in_city=4,
+ max_rails_between_cities=2,
+ max_rails_in_city=4,
),
schedule_generator=sparse_schedule_generator(speed_ration_map),
number_of_agents=20,
diff --git a/flatland/envs/rail_generators.py b/flatland/envs/rail_generators.py
index d98b9644411ebc00d3a765ed32d11d0f22fdcdd6..b132a5caeaaf1cd9c144b48eafeb016763d8bb42 100644
--- a/flatland/envs/rail_generators.py
+++ b/flatland/envs/rail_generators.py
@@ -4,7 +4,6 @@ import warnings
from typing import Callable, Tuple, Optional, Dict, List, Any
import msgpack
-import networkx as nx
import numpy as np
from flatland.core.grid.grid4_utils import get_direction, mirror
@@ -534,88 +533,74 @@ def random_rail_generator(cell_type_relative_proportion=[1.0] * 11) -> RailGener
return generator
-def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4, max_tracks_in_city=4,
- seed=0) -> RailGenerator:
+def sparse_rail_generator(max_num_cities: int = 5, grid_mode: bool = False, max_rails_between_cities: int = 4,
+ max_rails_in_city: int = 4, seed: int = 0) -> RailGenerator:
"""
Generates railway networks with cities and inner city rails
- :param num_cities: Number of city centers in the map
- :param grid_mode: Arange cities in a grid or randomly
- :param max_inter_city_rails: Maximum number of connecting rails going out from a city
- :param max_tracks_in_city: maximum number of internal rails
+ :param max_num_cities: Number of city centers in the map
+ :param grid_mode: arrange cities in a grid or randomly
+ :param max_rails_between_cities: Maximum number of connecting rails going out from a city
+ :param max_rails_in_city: maximum number of internal rails
:param seed: Random seed to initiate rail
:return: generator
"""
- G = nx.DiGraph()
DEBUG_PRINT_TIMING = False
- def generator(width, height, num_agents, num_resets=0) -> RailGeneratorProduct:
+ def generator(width: int, height: int, num_agents: int, num_resets: int = 0) -> RailGeneratorProduct:
+ np.random.seed(seed + num_resets)
rail_trans = RailEnvTransitions()
grid_map = GridTransitionMap(width=width, height=height, transitions=rail_trans)
- rail_array = grid_map.grid
- rail_array.fill(0)
- np.random.seed(seed + num_resets)
- # Graph to be able to create correct start/end pairs for schedule
+ city_radius = int(np.ceil((max_rails_in_city + 2) / 2.0)) + 1
- node_radius = int(np.ceil((max_tracks_in_city + 2) / 2.0)) + 1
- if 3 > max_tracks_in_city:
- rail_in_city = 3
- else:
- rail_in_city = max_tracks_in_city
- max_inter_city_rails_allowed = max_inter_city_rails
- if max_inter_city_rails_allowed > rail_in_city:
- max_inter_city_rails_allowed = rail_in_city
- # Generate a set of nodes for the sparse network
- # Try to connect cities to nodes first
- city_positions = []
- intersection_positions = []
-
- # Evenly distribute cities and intersections
+ min_nr_rails_in_city = 3
+ rails_in_city = min_nr_rails_in_city if max_rails_in_city < min_nr_rails_in_city else max_rails_in_city
+ rails_between_cities = rails_in_city if max_rails_between_cities > rails_in_city else max_rails_between_cities
+
+ # Evenly distribute cities
node_time_start = time.time()
- node_positions: List[Any] = None
- nb_nodes = num_cities
if grid_mode:
- node_positions, city_cells = _generate_node_positions_grid_mode(nb_nodes, node_radius, height, width)
+ city_positions, city_cells = _generate_evenly_distr_city_positions(max_num_cities, city_radius, width, height)
else:
- node_positions, city_cells = _generate_random_node_positions(nb_nodes, node_radius, height, width)
+ city_positions, city_cells = _generate_random_city_positions(max_num_cities, city_radius, width, height)
- # reduce nb_nodes, _num_cities, _num_intersections if less were generated in not_grid_mode
- nb_nodes = len(node_positions)
+ # reduce num_cities, _num_cities, _num_intersections if less were generated in not_grid_mode
+ num_cities = len(city_positions)
if DEBUG_PRINT_TIMING:
print("City position time", time.time() - node_time_start, "Seconds")
+
# Set up connection points for all cities
node_connection_time = time.time()
inner_connection_points, outer_connection_points, connection_info, city_orientations = _generate_node_connection_points(
- node_positions, node_radius, max_inter_city_rails_allowed,
- rail_in_city)
+ city_positions, city_radius, rails_between_cities,
+ rails_in_city)
if DEBUG_PRINT_TIMING:
print("Connection points", time.time() - node_connection_time)
# Connect the cities through the connection points
city_connection_time = time.time()
- inter_city_lines = _connect_cities(node_positions, outer_connection_points, connection_info, city_cells,
+ inter_city_lines = _connect_cities(city_positions, outer_connection_points, connection_info, city_cells,
rail_trans, grid_map)
if DEBUG_PRINT_TIMING:
print("City connection time", time.time() - city_connection_time)
# Build inner cities
city_build_time = time.time()
- through_tracks, free_tracks = _build_inner_cities(node_positions, inner_connection_points,
+ through_tracks, free_tracks = _build_inner_cities(city_positions, inner_connection_points,
outer_connection_points,
- node_radius,
+ city_radius,
rail_trans,
grid_map)
if DEBUG_PRINT_TIMING:
print("City build time", time.time() - city_build_time)
# Populate cities
train_station_time = time.time()
- train_stations, built_num_trainstation = _set_trainstation_positions(node_positions, node_radius, free_tracks,
+ train_stations, built_num_trainstation = _set_trainstation_positions(city_positions, city_radius, free_tracks,
grid_map)
if DEBUG_PRINT_TIMING:
print("Trainstation placing time", time.time() - train_station_time)
-
# Fix all transition elements
grid_fix_time = time.time()
_fix_transitions(city_cells, inter_city_lines, grid_map)
@@ -624,7 +609,7 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
# Generate start target pairs
schedule_time = time.time()
- agent_start_targets_nodes, num_agents = _generate_start_target_pairs(num_agents, nb_nodes, train_stations,
+ agent_start_targets_nodes, num_agents = _generate_start_target_pairs(num_agents, num_cities, train_stations,
city_orientations)
if DEBUG_PRINT_TIMING:
print("Schedule time", time.time() - schedule_time)
@@ -636,52 +621,50 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
'city_orientations': city_orientations
}}
- def _generate_random_node_positions(nb_nodes, node_radius, height, width):
+ def _generate_random_city_positions(num_cities: int, city_radius: int, width: int, height: int) -> (List[Tuple[int, int]], List[Tuple[int, int]]):
node_positions = []
city_cells = []
- for node_idx in range(nb_nodes):
+ for node_idx in range(num_cities):
to_close = True
tries = 0
while to_close:
- x_tmp = node_radius + 1 + np.random.randint(height - 2 * (node_radius + 1))
- y_tmp = node_radius + 1 + np.random.randint(width - 2 * (node_radius + 1))
+ x_tmp = city_radius + 1 + np.random.randint(height - 2 * (city_radius + 1))
+ y_tmp = city_radius + 1 + np.random.randint(width - 2 * (city_radius + 1))
to_close = False
# Check distance to nodes
for node_pos in node_positions:
- if _city_overlap((x_tmp, y_tmp), node_pos, 2 * (node_radius + 1) + 1):
+ if _city_overlap((x_tmp, y_tmp), node_pos, 2 * (city_radius + 1) + 1):
to_close = True
if not to_close:
node_positions.append((x_tmp, y_tmp))
- city_cells.extend(_city_cells(node_positions[-1], node_radius))
+ city_cells.extend(_city_cells(node_positions[-1], city_radius))
tries += 1
if tries > 200:
warnings.warn(
"Could not only set {} nodes after {} tries, although {} of nodes required to be generated!".format(
len(node_positions),
- tries, nb_nodes))
+ tries, num_cities))
break
- G.add_node(node_idx)
return node_positions, city_cells
- def _generate_node_positions_grid_mode(nb_nodes, node_radius, height, width):
+ def _generate_evenly_distr_city_positions(num_cities: int, city_radius: int, width: int, height: int) -> (List[Tuple[int, int]], List[Tuple[int, int]]):
nodes_ratio = height / width
- nodes_per_row = int(np.ceil(np.sqrt(nb_nodes * nodes_ratio)))
- nodes_per_col = int(np.ceil(nb_nodes / nodes_per_row))
- x_positions = np.linspace(node_radius + 1, height - node_radius - 2, nodes_per_row, dtype=int)
- y_positions = np.linspace(node_radius + 1, width - node_radius - 2, nodes_per_col, dtype=int)
+ nodes_per_row = int(np.ceil(np.sqrt(num_cities * nodes_ratio)))
+ nodes_per_col = int(np.ceil(num_cities / nodes_per_row))
+ x_positions = np.linspace(city_radius + 1, height - city_radius - 2, nodes_per_row, dtype=int)
+ y_positions = np.linspace(city_radius + 1, width - city_radius - 2, nodes_per_col, dtype=int)
node_positions = []
city_cells = []
- for node_idx in range(nb_nodes):
+ for node_idx in range(num_cities):
x_tmp = x_positions[node_idx % nodes_per_row]
y_tmp = y_positions[node_idx // nodes_per_row]
node_positions.append((x_tmp, y_tmp))
- city_cells.extend(_city_cells(node_positions[-1], node_radius))
- G.add_node(node_idx)
+ city_cells.extend(_city_cells(node_positions[-1], city_radius))
return node_positions, city_cells
def _generate_node_connection_points(node_positions, node_size, max_inter_city_rails_allowed, tracks_in_city=2):
@@ -745,7 +728,7 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
rail_trans, grid_map):
"""
Function to connect the different cities through their connection points
- :param node_positions: Positions of city centers
+ :param city_positions: Positions of city centers
:param connection_points: Boarder connection points of cities
:param connection_info: Number of connection points per direction NESW
:param rail_trans: Transitions
@@ -778,9 +761,6 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
new_line = connect_cities(rail_trans, grid_map, tmp_out_connection_point,
neighb_connection_point,
city_cells)
- G.add_edge(current_node, neighb_idx, direction=out_direction, length=len(new_line))
- G.add_edge(neighb_idx, current_node, direction=neighbour_direction, length=len(new_line))
-
all_paths.extend(new_line)
return all_paths
@@ -789,7 +769,7 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
grid_map):
"""
Builds inner city tracks. This current version connects all incoming connections to all outgoing connections
- :param node_positions: Positions of the cities
+ :param city_positions: Positions of the cities
:param inner_connection_points: Points on city boarder that are used to generate inner city track
:param outer_connection_points: Points where the city is connected to neighboring cities
:param rail_trans:
@@ -833,7 +813,7 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
def _set_trainstation_positions(node_positions, node_radius, free_tracks, grid_map):
"""
- :param node_positions:
+ :param city_positions:
:param num_trainstations:
:return:
"""
@@ -906,8 +886,8 @@ def sparse_rail_generator(num_cities=5, grid_mode=False, max_inter_city_rails=4,
def _closest_neigh_in_direction(current_node, node_positions):
"""
Returns indices of closest neighbours in every direction NESW
- :param current_node: Index of node in node_positions list
- :param node_positions: list of all points being considered
+ :param current_node: Index of node in city_positions list
+ :param city_positions: list of all points being considered
:return: list of index of closest neighbours in all directions
"""
node_dist = []
diff --git a/tests/test_flatland_envs_sparse_rail_generator.py b/tests/test_flatland_envs_sparse_rail_generator.py
index fd6e7b88562e88f13774ff07fdad8b663fcd5ab5..b94de82c4f7bdcda355316e65350c2b8b56a4ebe 100644
--- a/tests/test_flatland_envs_sparse_rail_generator.py
+++ b/tests/test_flatland_envs_sparse_rail_generator.py
@@ -13,7 +13,7 @@ from flatland.utils.rendertools import RenderTool
def test_sparse_rail_generator():
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=10, # Number of cities in map
+ rail_generator=sparse_rail_generator(max_num_cities=10, # Number of cities in map
num_intersections=10, # Number of interesections in map
num_trainstations=50, # Number of possible start/targets on map
min_node_dist=6, # Minimal distance of nodes
@@ -733,7 +733,7 @@ def test_sparse_rail_generator_deterministic():
env = RailEnv(width=25,
height=30,
- rail_generator=sparse_rail_generator(num_cities=5,
+ rail_generator=sparse_rail_generator(max_num_cities=5,
# Number of cities in map (where train stations are)
num_intersections=4,
# Number of intersections (no start / target)
@@ -1509,7 +1509,7 @@ def test_rail_env_action_required_info():
1. / 4.: 0.25} # Slow freight train
env_always_action = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=10, # Number of cities in map
+ rail_generator=sparse_rail_generator(max_num_cities=10, # Number of cities in map
num_intersections=10,
# Number of interesections in map
num_trainstations=50,
@@ -1528,7 +1528,7 @@ def test_rail_env_action_required_info():
np.random.seed(0)
env_only_if_action_required = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=10, # Number of cities in map
+ rail_generator=sparse_rail_generator(max_num_cities=10, # Number of cities in map
num_intersections=10,
# Number of interesections in map
num_trainstations=50,
@@ -1592,7 +1592,7 @@ def test_rail_env_malfunction_speed_info():
}
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=10, # Number of cities in map
+ rail_generator=sparse_rail_generator(max_num_cities=10, # Number of cities in map
num_intersections=10,
# Number of interesections in map
num_trainstations=50,
@@ -1640,7 +1640,7 @@ def test_sparse_generator_with_too_man_cities_does_not_break_down():
RailEnv(width=50,
height=50,
rail_generator=sparse_rail_generator(
- num_cities=100, # Number of cities in map
+ max_num_cities=100, # Number of cities in map
num_intersections=10, # Number of interesections in map
num_trainstations=50, # Number of possible start/targets on map
min_node_dist=6, # Minimal distance of nodes
diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py
index cc61150325ee86710ea3ee3820d8386c7b926da6..16f993a8373e8fb059c9b21af8e19fc06d53c517 100644
--- a/tests/test_flatland_malfunction.py
+++ b/tests/test_flatland_malfunction.py
@@ -165,7 +165,7 @@ def test_initial_malfunction():
env = RailEnv(width=25,
height=30,
- rail_generator=sparse_rail_generator(num_cities=5,
+ rail_generator=sparse_rail_generator(max_num_cities=5,
# Number of cities in map (where train stations are)
num_intersections=4,
# Number of intersections (no start / target)
@@ -247,7 +247,7 @@ def test_initial_malfunction_stop_moving():
env = RailEnv(width=25,
height=30,
- rail_generator=sparse_rail_generator(num_cities=5,
+ rail_generator=sparse_rail_generator(max_num_cities=5,
# Number of cities in map (where train stations are)
num_intersections=4,
# Number of intersections (no start / target)
@@ -339,7 +339,7 @@ def test_initial_malfunction_do_nothing():
env = RailEnv(width=25,
height=30,
- rail_generator=sparse_rail_generator(num_cities=5,
+ rail_generator=sparse_rail_generator(max_num_cities=5,
# Number of cities in map (where train stations are)
num_intersections=4,
# Number of intersections (no start / target)
@@ -430,7 +430,7 @@ def test_initial_nextmalfunction_not_below_zero():
env = RailEnv(width=25,
height=30,
- rail_generator=sparse_rail_generator(num_cities=5,
+ rail_generator=sparse_rail_generator(max_num_cities=5,
# Number of cities in map (where train stations are)
num_intersections=4,
# Number of intersections (no start / target)
diff --git a/tests/test_global_observation.py b/tests/test_global_observation.py
index 7213560f9e9873ea4488b96d30223bab8128b37b..7f8f62c0f028a9a679ba100ce749841ea96ba1ce 100644
--- a/tests/test_global_observation.py
+++ b/tests/test_global_observation.py
@@ -23,7 +23,7 @@ def test_get_global_observation():
env = RailEnv(width=50,
height=50,
- rail_generator=sparse_rail_generator(num_cities=25,
+ rail_generator=sparse_rail_generator(max_num_cities=25,
# Number of cities in map (where train stations are)
num_intersections=10,
# Number of intersections (no start / target)