"""
Stock 15-minute return prediction experiments.

This module provides dataset loading and experiment utilities for
stock 15-minute (intraday) return prediction.

Example:
    >>> from alpha_lab.stock_15m import Stock15mLoader
    >>>
    >>> loader = Stock15mLoader(
    ...     normalization_mode='dual',
    ...     positive_factor=1.0,
    ...     negative_factor=2.0
    ... )
    >>> dataset = loader.load(
    ...     dt_range=['2020-01-01', '2023-12-31'],
    ...     feature_path='/data/parquet/stock_1min_alpha158',
    ...     kline_path='/data/parquet/stock_1min_kline'
    ... )
    >>>
    >>> # Extract training data
    >>> X_train, y_train, w_train = dataset.to_numpy()

Training:
    >>> from alpha_lab.stock_15m import train_model, TrainConfig
    >>>
    >>> config = TrainConfig(
    ...     dt_range=['2020-01-01', '2023-12-31'],
    ...     feature_path='/data/parquet/stock_1min_alpha158',
    ...     kline_path='/data/parquet/stock_1min_kline'
    ... )
    >>> model, metrics = train_model(config, output_dir='results/exp01')
"""

# Re-export all public APIs from src submodules
from .src import Stock15mLoader

try:
    from .src import train_model, TrainConfig
    __all__ = ['Stock15mLoader', 'train_model', 'TrainConfig']
except ImportError:
    # xgboost or sklearn not installed
    __all__ = ['Stock15mLoader']