Index

A

accepted_metrics() (FixedForecast static method) (RollingForecast static method) (Strategy static method) actor_id (RayTask attribute) ACTUAL_DATA (FieldNames attribute)

add() (ResultCollector method) add_worker_initializer() (RayBackend method) (SequentialBackend method) all_fields() (FieldNames class method) annotate() (in module ts_benchmark.models.model_base)

B

batch_forecast() (DUET method) (FITS method) (ModelBase method) (Pathformer method) (PDF method) (TransformerAdapter method)

BatchMaker (class in ts_benchmark.models.model_base) build_result_df() (in module ts_benchmark.evaluation.evaluate_model)

C

clear_data() (Dataset method) close() (RayActorPool method) (RayBackend method) (SequentialBackend method)

collect() (EvalResult method) (ResultCollector method) compress() (in module ts_benchmark.utils.compress) compress_gz() (in module ts_benchmark.utils.compress) compress_gzip() (in module ts_benchmark.utils.compress)

D

darts_deep_model_adapter() (in module ts_benchmark.baselines.darts.darts_models) darts_regression_model_adapter() (in module ts_benchmark.baselines.darts.darts_models) darts_statistical_model_adapter() (in module ts_benchmark.baselines.darts.darts_models) DartsConfig (class in ts_benchmark.baselines.darts.darts_models) DartsModelAdapter (class in ts_benchmark.baselines.darts.darts_models) DataPool (class in ts_benchmark.data.data_pool) DataPoolImpl (class in ts_benchmark.data.data_pool_impl_base) DataServer (class in ts_benchmark.data.data_server_base) Dataset (class in ts_benchmark.data.dataset) dataset (DataSource property) DATASET_CLASS (DataSource attribute) DatasetForTransformer (class in ts_benchmark.baselines.utils) DatasetInfo (class in ts_benchmark.pipeline) DataSource (class in ts_benchmark.data.data_source)

datasrc_class (DatasetInfo attribute) decompose_time() (in module ts_benchmark.baselines.utils) decompress() (in module ts_benchmark.utils.compress) decompress_gz() (in module ts_benchmark.utils.compress) decompress_gzip() (in module ts_benchmark.utils.compress) DEFAULT_CONFIG_KEY (Strategy attribute) default_result() (Evaluator method) detect_fit() (MerlionModelAdapter method) detect_hyper_param_tune() (DUET method) (Pathformer method) (PDF method) detect_label() (MerlionModelAdapter method) detect_score() (MerlionModelAdapter method) DUET (class in ts_benchmark.baselines.duet)

E

encode_params() (in module ts_benchmark.evaluation.evaluator) env (RayBackend property) (SequentialBackend property) eval_model() (in module ts_benchmark.evaluation.evaluate_model) EvalResult (class in ts_benchmark.evaluation.evaluate_model) evaluate() (Evaluator method)

evaluate_with_log() (Evaluator method) Evaluator (class in ts_benchmark.evaluation.evaluator) execute() (ForecastingStrategy method) (Strategy method) execute_on_workers() (RayBackend method) (SequentialBackend method)

F

field_names (FixedForecast property) (RollingForecast property) (Strategy property) FieldNames (class in ts_benchmark.evaluation.strategy.constants) FILE_NAME (FieldNames attribute) filter_data() (in module ts_benchmark.pipeline) find_length() (in module ts_benchmark.evaluation.metrics.utils) find_record_files() (in module ts_benchmark.recording) FIT_TIME (FieldNames attribute) FITS (class in ts_benchmark.baselines.fits.fits) fix_all_random_seed() (in module ts_benchmark.utils.random_utils) fix_random_seed() (in module ts_benchmark.utils.random_utils) FixedForecast (class in ts_benchmark.evaluation.strategy.fixed_forecast) forecast() (DartsModelAdapter method) (DUET method) (FITS method) (ModelBase method) (Pathformer method) (PDF method) (TransformerAdapter method) (VAR method)

forecast_fit() (DartsModelAdapter method) (DUET method) (FITS method) (ModelBase method) (Pathformer method) (PDF method) (TransformerAdapter method) (VAR method) forecasting_data_provider() (in module ts_benchmark.baselines.utils) ForecastingStrategy (class in ts_benchmark.evaluation.strategy.forecasting) format_data_columns() (in module ts_benchmark.report.report_dash.layout)

G

generate_layout() (in module ts_benchmark.report.report_dash.layout) generate_model_factory() (in module ts_benchmark.baselines.merlion.merlion_models) (in module ts_benchmark.baselines.time_series_library.adapters_for_transformers) get() (DartsConfig method) (ObjectRefStorageActor method) (RaySharedStorage method) (SequentialSharedStorage method) (SharedStorage method) get_collector() (Strategy method) get_compress_file_ext() (in module ts_benchmark.utils.compress) get_compress_method_from_ext() (in module ts_benchmark.utils.compress) get_config_str() (Strategy method) get_darts_class_params() (DartsConfig method) get_default_result() (Strategy method) get_leaderboard() (in module ts_benchmark.report.utils.leaderboard) get_list_anomaly() (in module ts_benchmark.evaluation.metrics.utils)

get_model_hyper_params() (in module ts_benchmark.models.model_loader) get_model_info() (in module ts_benchmark.models.model_loader) get_models() (in module ts_benchmark.models.model_loader) get_pool() (DataPool method) get_required_configs() (Strategy class method) get_series() (DataPoolImpl method) (Dataset method) (GlobalStorageDataPool method) get_series_meta_info() (DataPoolImpl method) (Dataset method) (GlobalStorageDataPool method) get_size() (ResultCollector method) get_state() (Dataset method) get_time_mark() (in module ts_benchmark.baselines.utils) get_unique_file_suffix() (in module ts_benchmark.utils.get_file_name) GlobalStorageDataPool (class in ts_benchmark.data.suites.global_storage) GlobalStorageDataServer (class in ts_benchmark.data.suites.global_storage)

H

has_more_batches() (RollingForecastEvalBatchMaker method) (RollingForecastPredictBatchMaker method)

has_series() (Dataset method) has_series_meta_info() (Dataset method)

I

import_model_info() (in module ts_benchmark.models.model_loader) INFERENCE_DATA (FieldNames attribute) INFERENCE_TIME (FieldNames attribute)

init() (RayBackend method) (SequentialBackend method) is_actor() (in module ts_benchmark.utils.parallel.ray_backend)

L

load_record_data() (in module ts_benchmark.recording) load_series_info() (in module ts_benchmark.data.utils) load_series_list() (DataSource method) (LocalDataSource method)

LocalDataSource (class in ts_benchmark.data.data_source) LocalForecastingDataSource (class in ts_benchmark.data.data_source) LOG_INFO (FieldNames attribute)

M

mae() (in module ts_benchmark.evaluation.metrics.regression_metrics) mae_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) make_batch() (BatchMaker method) (RollingForecastPredictBatchMaker method) make_batch_eval() (RollingForecastEvalBatchMaker method) make_batch_predict() (RollingForecastEvalBatchMaker method) mape() (in module ts_benchmark.evaluation.metrics.regression_metrics) mape_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) mase() (in module ts_benchmark.evaluation.metrics.regression_metrics) mase_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) MerlionModelAdapter (class in ts_benchmark.baselines.merlion.merlion_models) metadata (Dataset property) model_name (DartsModelAdapter property) (DUET property) MODEL_NAME (FieldNames attribute) model_name (FITS property) (ModelBase property) (Pathformer property) (PDF property) (TransformerAdapter property) (VAR property) MODEL_PARAMS (FieldNames attribute) ModelBase (class in ts_benchmark.models.model_base) ModelFactory (class in ts_benchmark.models.model_loader) module ts_benchmark.baselines.darts.darts_models, [1] ts_benchmark.baselines.duet ts_benchmark.baselines.duet.duet ts_benchmark.baselines.fits.fits, [1] ts_benchmark.baselines.merlion.merlion_models, [1] ts_benchmark.baselines.pathformer.pathformer, [1] ts_benchmark.baselines.pdf ts_benchmark.baselines.pdf.PDF ts_benchmark.baselines.self_impl.VAR.VAR, [1] ts_benchmark.baselines.time_series_library.adapters_for_transformers, [1] ts_benchmark.baselines.utils, [1] ts_benchmark.common.constant ts_benchmark.data.data_pool, [1] ts_benchmark.data.data_pool_impl_base, [1] ts_benchmark.data.data_server_base, [1] ts_benchmark.data.data_source, [1] ts_benchmark.data.dataset, [1] ts_benchmark.data.suites.global_storage, [1] ts_benchmark.data.utils, [1] ts_benchmark.evaluation.evaluate_model, [1] ts_benchmark.evaluation.evaluator, [1] ts_benchmark.evaluation.metrics.regression_metrics, [1] ts_benchmark.evaluation.metrics.utils, [1] ts_benchmark.evaluation.strategy.constants, [1] ts_benchmark.evaluation.strategy.fixed_forecast, [1] ts_benchmark.evaluation.strategy.forecasting, [1] ts_benchmark.evaluation.strategy.rolling_forecast, [1] ts_benchmark.evaluation.strategy.strategy, [1] ts_benchmark.models.model_base, [1] ts_benchmark.models.model_loader, [1] ts_benchmark.pipeline, [1] ts_benchmark.recording, [1] ts_benchmark.report.report_csv, [1] ts_benchmark.report.report_dash.app, [1] ts_benchmark.report.report_dash.layout, [1] ts_benchmark.report.report_dash.memory ts_benchmark.report.utils.leaderboard, [1] ts_benchmark.utils.compress, [1] ts_benchmark.utils.data_processing, [1] ts_benchmark.utils.design_pattern, [1] ts_benchmark.utils.get_file_name, [1] ts_benchmark.utils.parallel.base, [1] ts_benchmark.utils.parallel.ray_backend, [1] ts_benchmark.utils.parallel.sequential_backend, [1] ts_benchmark.utils.random_utils, [1]

mse() (in module ts_benchmark.evaluation.metrics.regression_metrics) mse_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) msmape() (in module ts_benchmark.evaluation.metrics.regression_metrics) msmape_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) multi_forecasting_hyper_param_tune() (DUET method) (FITS method) (Pathformer method) (PDF method) (TransformerAdapter method)

O

ObjectRefStorageActor (class in ts_benchmark.utils.parallel.ray_backend)

P

padding_data_for_forecast() (DUET method) (FITS method) (Pathformer method) (PDF method) (TransformerAdapter method) Pathformer (class in ts_benchmark.baselines.pathformer.pathformer) PDF (class in ts_benchmark.baselines.pdf) pipeline() (in module ts_benchmark.pipeline)

pred_len (TransformerConfig property), [1], [2] put() (ObjectRefStorageActor method) (RayResult method) (RaySharedStorage method) (SequentialResult method) (SequentialSharedStorage method) (SharedStorage method) (TaskResult method)

R

RayActor (class in ts_benchmark.utils.parallel.ray_backend) RayActorPool (class in ts_benchmark.utils.parallel.ray_backend) RayBackend (class in ts_benchmark.utils.parallel.ray_backend) RayResult (class in ts_benchmark.utils.parallel.ray_backend) RaySharedStorage (class in ts_benchmark.utils.parallel.ray_backend) RayTask (class in ts_benchmark.utils.parallel.ray_backend) read_data() (in module ts_benchmark.data.utils) read_record_file() (in module ts_benchmark.recording) report() (in module ts_benchmark.report.report_csv) (in module ts_benchmark.report.report_dash.app) REQUIRED_CONFIGS (FixedForecast attribute) (ForecastingStrategy attribute) (RollingForecast attribute) (Strategy attribute) required_hyper_params() (DUET static method) (FITS static method) (Pathformer static method) (PDF static method) (TransformerAdapter static method) (VAR static method)

reset() (ResultCollector method) result (RayTask attribute) result() (RayResult method) (SequentialResult method) (TaskResult method) ResultCollector (class in ts_benchmark.evaluation.strategy.strategy) rmse() (in module ts_benchmark.evaluation.metrics.regression_metrics) rmse_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) RollingForecast (class in ts_benchmark.evaluation.strategy.rolling_forecast) RollingForecastEvalBatchMaker (class in ts_benchmark.evaluation.strategy.rolling_forecast) RollingForecastPredictBatchMaker (class in ts_benchmark.evaluation.strategy.rolling_forecast) run() (RayActor method)

S

save_log() (in module ts_benchmark.recording) schedule() (RayActorPool method) (RayBackend method) (SequentialBackend method) SequentialBackend (class in ts_benchmark.utils.parallel.sequential_backend) SequentialResult (class in ts_benchmark.utils.parallel.sequential_backend) SequentialSharedStorage (class in ts_benchmark.utils.parallel.sequential_backend) set_data() (Dataset method) set_pool() (DataPool method) set_state() (Dataset method) shared_storage (RayBackend property) (SequentialBackend property) SharedStorage (class in ts_benchmark.utils.parallel.base) single_forecasting_hyper_param_tune() (DUET method) (FITS method) (Pathformer method) (PDF method) (TransformerAdapter method)

Singleton (class in ts_benchmark.utils.design_pattern) size_value (DatasetInfo attribute) SlidingWindowDataLoader (class in ts_benchmark.baselines.utils) smape() (in module ts_benchmark.evaluation.metrics.regression_metrics) smape_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) split_before() (in module ts_benchmark.utils.data_processing) start_async() (DataServer method) (GlobalStorageDataServer method) start_time (RayTask attribute) start_time() (RayActor method) Strategy (class in ts_benchmark.evaluation.strategy.strategy) STRATEGY_ARGS (FieldNames attribute) sync_data() (GlobalStorageDataPool method) (in module ts_benchmark.data.suites.global_storage)

T

TaskResult (class in ts_benchmark.utils.parallel.base) timeout (RayTask attribute) train_val_split() (in module ts_benchmark.baselines.utils) transformer_adapter() (in module ts_benchmark.baselines.time_series_library.adapters_for_transformers) TransformerAdapter (class in ts_benchmark.baselines.time_series_library.adapters_for_transformers) TransformerConfig (class in ts_benchmark.baselines.fits.fits) (class in ts_benchmark.baselines.pathformer.pathformer) (class in ts_benchmark.baselines.time_series_library.adapters_for_transformers) ts_benchmark.baselines.darts.darts_models module, [1] ts_benchmark.baselines.duet module ts_benchmark.baselines.duet.duet module ts_benchmark.baselines.fits.fits module, [1] ts_benchmark.baselines.merlion.merlion_models module, [1] ts_benchmark.baselines.pathformer.pathformer module, [1] ts_benchmark.baselines.pdf module ts_benchmark.baselines.pdf.PDF module ts_benchmark.baselines.self_impl.VAR.VAR module, [1] ts_benchmark.baselines.time_series_library.adapters_for_transformers module, [1] ts_benchmark.baselines.utils module, [1] ts_benchmark.common.constant module ts_benchmark.data.data_pool module, [1] ts_benchmark.data.data_pool_impl_base module, [1] ts_benchmark.data.data_server_base module, [1] ts_benchmark.data.data_source module, [1] ts_benchmark.data.dataset module, [1] ts_benchmark.data.suites.global_storage module, [1] ts_benchmark.data.utils module, [1] ts_benchmark.evaluation.evaluate_model module, [1] ts_benchmark.evaluation.evaluator module, [1]

ts_benchmark.evaluation.metrics.regression_metrics module, [1] ts_benchmark.evaluation.metrics.utils module, [1] ts_benchmark.evaluation.strategy.constants module, [1] ts_benchmark.evaluation.strategy.fixed_forecast module, [1] ts_benchmark.evaluation.strategy.forecasting module, [1] ts_benchmark.evaluation.strategy.rolling_forecast module, [1] ts_benchmark.evaluation.strategy.strategy module, [1] ts_benchmark.models.model_base module, [1] ts_benchmark.models.model_loader module, [1] ts_benchmark.pipeline module, [1] ts_benchmark.recording module, [1] ts_benchmark.report.report_csv module, [1] ts_benchmark.report.report_dash.app module, [1] ts_benchmark.report.report_dash.layout module, [1] ts_benchmark.report.report_dash.memory module ts_benchmark.report.utils.leaderboard module, [1] ts_benchmark.utils.compress module, [1] ts_benchmark.utils.data_processing module, [1] ts_benchmark.utils.design_pattern module, [1] ts_benchmark.utils.get_file_name module, [1] ts_benchmark.utils.parallel.base module, [1] ts_benchmark.utils.parallel.ray_backend module, [1] ts_benchmark.utils.parallel.sequential_backend module, [1] ts_benchmark.utils.random_utils module, [1]

U

update_data() (Dataset method)

update_meta_index() (LocalDataSource method)

V

validate() (DUET method) (FITS method) (Pathformer method) (PDF method) (TransformerAdapter method)

VAR (class in ts_benchmark.baselines.self_impl.VAR.VAR) VAR_model (in module ts_benchmark.baselines.self_impl.VAR.VAR)

W

wait() (RayActorPool method) wape() (in module ts_benchmark.evaluation.metrics.regression_metrics)

wape_norm() (in module ts_benchmark.evaluation.metrics.regression_metrics) write_record_file() (in module ts_benchmark.recording)