from .types import RawConfig, Config

def get_dev_config() -> RawConfig:
  
    classification_models = ["LogisticRegression_two_class"]

    return RawConfig(
        directional_models_meta = False,
        dimensionality_reduction = False,
        n_features_to_select = 30,
        expanding_window_base = False,
        expanding_window_meta = False,
        sliding_window_size_base = 380,
        sliding_window_size_meta = 1,
        retrain_every = 20,
        scaler = 'minmax', # 'normalize' 'minmax' 'standardize'

        assets = ['daily_only_btc'],
        target_asset = 'BTC_USD',
        other_assets = [],
        exogenous_data = [],
        load_non_target_asset= True,
        own_features = ['level_2', 'date_days'],
        other_features = ['single_mom'],
        exogenous_features = ['z_score'],

        directional_models = classification_models,
        meta_models = [],

        event_filter = 'none',
        labeling = 'two_class',
        forecasting_horizon = 100,
    )


def get_default_ensemble_config() -> RawConfig:
  
    classification_models = ["LogisticRegression_two_class", "LDA", "NB", "RFC", "XGB_two_class", "LGBM", "StaticMom"]
    meta_models = ['LogisticRegression_two_class', 'LGBM']

    return RawConfig(
        directional_models_meta = True,
        dimensionality_reduction = False,
        n_features_to_select = 30,
        expanding_window_base = False,
        expanding_window_meta = True,
        sliding_window_size_base = 380,
        sliding_window_size_meta = 240,
        retrain_every = 10,
        scaler = 'minmax', # 'normalize' 'minmax' 'standardize'

        assets = ['daily_crypto'],
        target_asset = 'BTC_USD',
        other_assets = ['daily_etf'],
        exogenous_data = ['daily_glassnode'],
        load_non_target_asset= True,
        own_features = ['level_2', 'date_days', 'lags_up_to_5'],
        other_features = ['level_2', 'lags_up_to_5'],
        exogenous_features = ['z_score'],

        directional_models = classification_models,
        meta_models = meta_models,

        event_filter = 'cusum_vol',
        labeling = 'two_class',
        forecasting_horizon = 100,
    )



def get_lightweight_ensemble_config() -> RawConfig:
  
    classification_models = ['LogisticRegression_two_class', 'LGBM']
    meta_models = ['LogisticRegression_two_class', 'LGBM']

    return RawConfig(
        directional_models_meta = True,
        dimensionality_reduction = True,
        n_features_to_select = 30,
        expanding_window_base = True,
        expanding_window_meta = True,
        sliding_window_size_base = 3800,
        sliding_window_size_meta = 2400,
        retrain_every = 1000,
        scaler = 'minmax', # 'normalize' 'minmax' 'standardize'

        assets = ['fivemin_crypto'],
        target_asset = 'BTC_USD',
        other_assets = [],
        exogenous_data = [],
        load_non_target_asset= False,
        own_features = ['level_1'],
        other_features = [],
        exogenous_features = [],

        directional_models = classification_models,
        meta_models = meta_models,

        event_filter = 'cusum_fixed',
        labeling = 'two_class',
        forecasting_horizon = 50,
    )


