citylearn.end_use_load_profiles.neighborhood module

class citylearn.end_use_load_profiles.neighborhood.Neighborhood(weather_data: str = None, year_of_publication: int = None, release: int = None, cache: bool = None, energyplus_output_directory: Path | str = None, dataset_directory: Path | str = None, max_workers: int = None, random_seed: int = None)[source]

Bases: object

build(idd_filepath: Path | str, bldg_ids: List[int] = None, include_lstm_models: bool = None, test_lstm_models: bool = None, test_citylearn_simulation: bool = None, delete_energyplus_simulation_output: bool = None, sample_buildings_kwargs: Mapping[str, Any] = None, energyplus_simulation_kwargs: Mapping[str, Any] = None, train_lstm_kwargs: Mapping[str, Any] = None, schema_kwargs: Mapping[str, Any] = None, test_citylearn_simulation_kwargs: Mapping[str, Any] = None) NeighborhoodBuild[source]
property dataset_directory: Path | str
delete_energyplus_simulation_output(simulators: Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]])[source]
property end_use_load_profiles: EndUseLoadProfiles
property energyplus_output_directory: Path | str
get_lstm_training_data(simulators: Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]]) Mapping[int, DataFrame][source]
get_weather_data(simulator: EndUseLoadProfilesEnergyPlusPartialLoadSimulator, shifts: Tuple[int, int, int] = None, accuracy: Mapping[str, Tuple[float, float, float]] = None) DataFrame[source]
property max_workers: int
multiprocess_test_lstm(training_data: Mapping[int, DataFrame], schema_filepath: Path) Mapping[int, DataFrame][source]
property random_seed: int
sample_buildings(filters: Mapping[str, List[Any]] = None, sample_method: SampleMethod = None, sample_count: int = None, duplicate_to_count: bool = None, single_county: bool = None, single_family_detached: bool = None, **kwargs) Tuple[List[int], List[int], Mapping[str, Any]][source]
set_schema(simulators: Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]], lstm_models: Mapping[int, Mapping[str, Any]] = None, template: Mapping[str, dict | float | int | str] = None, metadata: DataFrame = None, dataset_name: str = None, schema_directory: Path | str = None, weather_kwargs: dict = None) Path[source]
simulate_energy_plus(bldg_ids: List[int], idd_filepath: Path | str, simulation_ids: List[str] = None, models: List[Path | str] = None, schedules: Path | DataFrame = None, osm: bool = None, partial_loads_simulations: int = None, partial_loads_kwargs: Mapping[str, Any] = None, **kwargs) Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]][source]
test_citylearn_simulation(schema: Path, model: Agent = None, env_kwargs: Mapping[str, Any] = None, model_kwargs: Mapping[str, Any] = None, report_lstm_performance: bool = None) Tuple[DataFrame, Mapping[int, DataFrame], Mapping[int, DataFrame]][source]
test_lstm(bldg_id: int, training_data: DataFrame, schema_filepath: Path, bldg_key: str = None) Tuple[int, DataFrame][source]
train_lstm(data: Mapping[int, DataFrame], config: Mapping[str, Any] = None, seed: int = None) Mapping[int, Mapping[str, Any]][source]
class citylearn.end_use_load_profiles.neighborhood.NeighborhoodBuild(schema_filepath: Path, citylearn_simulation_test_evaluation: DataFrame, citylearn_simulation_lstm_prediction_data: Mapping[int, DataFrame], citylearn_simulation_lstm_error_data: Mapping[int, DataFrame], lstm_test_data: Mapping[int, DataFrame], bldg_ids: List[int], sample_cluster_labels: List[int], sample_metadata: Mapping[str, Any], simulators: Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]])[source]

Bases: object

property bldg_ids: List[int]
property citylearn_simulation_lstm_error_data: Mapping[int, DataFrame]
property citylearn_simulation_lstm_prediction_data: Mapping[int, DataFrame]
property citylearn_simulation_test_evaluation: DataFrame
property lstm_test_data: Mapping[int, DataFrame]
property sample_cluster_labels: List[int]
property sample_metadata: Mapping[str, Any]
property schema_filepath: Path
property simulators: Mapping[int, Mapping[str, EndUseLoadProfilesEnergyPlusSimulator | List[EndUseLoadProfilesEnergyPlusPartialLoadSimulator]]]
class citylearn.end_use_load_profiles.neighborhood.SampleMethod(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]

Bases: Enum

METADATA_CLUSTER_FREQUENCY = 1
RANDOM = 0