cleaning and bug fixing

freqtrade/freqai/data_handler.py

@@ -19,6 +19,7 @@ class DataHandler:
     """
     Class designed to handle all the data for the IFreqaiModel class model. 
     Functionalities include holding, saving, loading, and analyzing the data.
+    author: Robert Caulk, rob.caulk@gmail.com
     """
 
     def __init__(self, config: Dict[str, Any], dataframe: DataFrame, data: List):
@@ -32,6 +33,10 @@ class DataHandler:
         self.data_dictionary = {}
         self.config = config
         self.freq_config = config['freqai']
+        self.predictions = np.array([])
+        self.do_predict = np.array([])
+        self.target_mean = np.array([])
+        self.target_std = np.array([])
 
     def save_data(self, model: Any) -> None:
         """

freqtrade/freqai/freqai_interface.py

@@ -17,6 +17,7 @@ class IFreqaiModel(ABC):
     User models should inherit from this class as shown in 
     templates/ExamplePredictionModel.py where the user overrides
     train(), predict(), fit(), and make_labels().
+    Author: Robert Caulk, rob.caulk@gmail.com
     """
 
     def __init__(self, config: Dict[str, Any]) -> None:
@@ -104,10 +105,10 @@ class IFreqaiModel(ABC):
 
         return dataframe
 
-    def train(self, unfiltered_dataframe: DataFrame, metadata: dict) -> Tuple[DataFrame, DataFrame]:
+    def train(self, unfiltered_dataframe: DataFrame, metadata: dict) -> Any:
         """
         Filter the training data and train a model to it. Train makes heavy use of the datahandler
-        for storing, saving, loading, and managed.
+        for storing, saving, loading, and analyzing the data.
         :params:
         :unfiltered_dataframe: Full dataframe for the current training period
         :metadata: pair metadata from strategy. 
@@ -115,7 +116,7 @@ class IFreqaiModel(ABC):
         :model: Trained model which can be used to inference (self.predict)
         """
 
-        return unfiltered_dataframe, unfiltered_dataframe
+        return Any
 
     def fit(self) -> Any:
         """