made it possible to train model with existing data

alphamind/model/composer.py

@@ -105,8 +105,11 @@ class DataMeta(object):
 
 def train_model(ref_date: str,
                 alpha_model: ModelBase,
-                data_meta: DataMeta):
+                data_meta: DataMeta=None,
+                x_values: pd.DataFrame=None,
+                y_values: pd.DataFrame=None):
     base_model = copy.deepcopy(alpha_model)
+    if x_values is None:
         train_data = fetch_train_phase(data_meta.engine,
                                        alpha_model.formulas,
                                        ref_date,
@@ -127,7 +130,10 @@ def train_model(ref_date: str,
 
 def predict_by_model(ref_date: str,
                      alpha_model: ModelBase,
-                     data_meta: DataMeta):
+                     data_meta: DataMeta=None,
+                     x_values: pd.DataFrame=None,
+                     codes: Iterable[int]=None):
+    if x_values is None:
         predict_data = fetch_predict_phase(data_meta.engine,
                                            alpha_model.formulas,
                                            ref_date,