added fit to dfh

myresources/crocodile/deeplearning_df.py

@@ -149,6 +149,12 @@ def __init__(self, scaler: Union[RobustScaler, StandardScaler], imputer: SimpleI
         self.imputer: SimpleImputer = imputer
         self.scaler: Union[RobustScaler, StandardScaler] = scaler
 
+    @property
+    def cols_encoded(self):
+        """all numerical columns to be used as inputs to the model. Used in getstate, setstate, design model, etc."""
+        onehot_names: list[str] = list(self.encoder_onehot.get_feature_names_out())
+        return onehot_names + self.cols_ordinal + self.cols_numerical
+
     def __getstate__(self):
         atts: list[str] = ["scaler", "imputer", "cols_numerical", "cols_ordinal", "cols_onehot", "encoder_onehot", "encoder_ordinal", "clipper_categorical", "clipper_numerical"]
         res = {}
@@ -206,12 +212,6 @@ def clip_encode_impute_scale(self, df: 'pd.DataFrame', precision: str) -> 'pd.Da
         df = self.impute_standardize(df=df)
         return df
 
-    @property
-    def encoded_columns(self):
-        """all numerical columns to be used as inputs to the model. Used in getstate, setstate, design model, etc."""
-        onehot_names: list[str] = list(self.encoder_onehot.get_feature_names_out())
-        return onehot_names + self.cols_ordinal + self.cols_numerical
-
 
 def check_for_nan(ip: 'npt.NDArray[Any]') -> int:
     assert len(ip.shape) == 2, f"Expected 2D array, but got {len(ip.shape)}D array"