diff --git a/auto_trading/predictor/__init__.py b/auto_trading/predictor/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/auto_trading/predictor/mean_agg.py b/auto_trading/predictor/mean_agg.py deleted file mode 100644 index 75bc421..0000000 --- a/auto_trading/predictor/mean_agg.py +++ /dev/null @@ -1,16 +0,0 @@ -import pandas as pd # type: ignore - -from ..interfaces import Predictor - - -class MeanAggregator(Predictor): - """Aggregate multiples predictors.""" - - def __init__(self, predictors): - """Initialize MeanAggregator.""" - self.predictors = predictors - - def predict(self, data: pd.DataFrame) -> dict: - """Predict from others predictors.""" - preds = [cls.predict(data) for cls in self.predictors] - return pd.DataFrame(preds).mean().to_dict() diff --git a/auto_trading/predictor/normalized.py b/auto_trading/predictor/normalized.py deleted file mode 100644 index 2946823..0000000 --- a/auto_trading/predictor/normalized.py +++ /dev/null @@ -1,11 +0,0 @@ -import pandas as pd # type: ignore - -from ..interfaces import Predictor - - -class NormalizedPredictor(Predictor): - def predict(self, data: pd.DataFrame) -> dict: - """It's just random""" - df = data.iloc[-1] - df = df/df.sum() - return df.to_dict() diff --git a/auto_trading/predictor/random_predictor.py b/auto_trading/predictor/random_predictor.py deleted file mode 100644 index e3fcb40..0000000 --- a/auto_trading/predictor/random_predictor.py +++ /dev/null @@ -1,13 +0,0 @@ -from random import random -import pandas as pd # type: ignore - -from ..interfaces import Predictor - - -class RandomPredictor(Predictor): - def predict(self, data: pd.DataFrame) -> dict: - """It's just random""" - return { - k: random()*2-1 - for k in data.columns - } diff --git a/auto_trading/predictor/selector.py b/auto_trading/predictor/selector.py deleted file mode 100644 index a286cd5..0000000 --- a/auto_trading/predictor/selector.py +++ /dev/null @@ -1,13 +0,0 @@ -import pandas as pd # type: ignore - -from ..interfaces import Predictor - - -class SelectorPredictor(Predictor): - - def __init__(self, to_return) -> None: - self.to_return = to_return - - def predict(self, data: pd.DataFrame) -> dict: - """It's just random""" - return {**{k:0 for k in data.to_dict().keys()}, **self.to_return}