flatland.env_generation.env_generator module

flatland.env_generation.env_generator.env_generator(n_agents=7, x_dim=30, y_dim=30, n_cities=2, max_rail_pairs_in_city=4, grid_mode=False, max_rails_between_cities=2, malfunction_duration_min=20, malfunction_duration_max=50, malfunction_interval=540, speed_ratios=None, seed=42, obs_builder_object=None, acceleration_delta=1.0, braking_delta=-1.0, rewards: Rewards | None = None, effects_generator: EffectsGenerator[RailEnv] | None = None) → Tuple[RailEnv, Dict, Dict]

Create an env with a given spec using sparse_rail_generator. Defaults are taken from Flatland 3 Round 2 Test_0, see `Environment Configurations <https://flatland.aicrowd.com/challenges/flatland3/envconfig.html`_. Parameters name come from metadata.csv in debug-environments.zip

Parameters

n_agents: int

number of agents

x_dim: int

number of columns

y_dim: int

number of rows

n_cities: int

Max number of cities to build. The generator tries to achieve this numbers given all the parameters. Goes into sparse_rail_generator.

max_rail_pairs_in_city: int

Number of parallel tracks in the city. This represents the number of tracks in the train stations. Goes into sparse_rail_generator.

grid_mode: bool

How to distribute the cities in the path, either equally in a grid or random. Goes into sparse_rail_generator.

max_rails_between_cities: int

Max number of rails connecting to a city. This is only the number of connection points at city boarder.

malfunction_duration_min: int

Minimal duration of malfunction. Goes into ParamMalfunctionGen.

malfunction_duration_max: int

Max duration of malfunction. Goes into ParamMalfunctionGen.

malfunction_interval: int

Inverse of rate of malfunction occurrence. Goes into ParamMalfunctionGen.

speed_ratios: Dict[float, float]

Speed ratios of all agents. They are probabilities of all different speeds and have to add up to 1. Goes into sparse_line_generator. Defaults to {1.0: 0.25, 0.5: 0.25, 0.33: 0.25, 0.25: 0.25}.

seed: int

Initiate random seed generators. Goes into reset.

obs_builder_object: Optional[ObservationBuilder]

Defaults to TreeObsForRailEnv(max_depth=3, predictor=ShortestPathPredictorForRailEnv(max_depth=50))

Returns

RailEnv

The generated environment reset with the given seed.

observationsDict

Initial observations from reset()

infoDict

Initial infos from reset()