diff --git a/src/data_handler/station_preparation.py b/src/data_handler/station_preparation.py
index da8c3ad83bc3c794e540863f6343b7337484ee7d..42d94e277415c637d4fc9a5262692a6b3150b0a7 100644
--- a/src/data_handler/station_preparation.py
+++ b/src/data_handler/station_preparation.py
@@ -95,13 +95,29 @@ class StationPrep(AbstractStationPrep):
         return self.data.shape, self.get_X().shape, self.get_Y().shape
 
     def __repr__(self):
-        return f"StationPrep(station={self.station}, data_path='{self.path}, " \
+        return f"StationPrep(station={self.station}, data_path='{self.path}', " \
                f"statistics_per_var={self.statistics_per_var}, " \
                f"station_type='{self.station_type}', network='{self.network}', " \
                f"sampling='{self.sampling}', target_dim='{self.target_dim}', target_var='{self.target_var}', " \
                f"interpolate_dim='{self.interpolate_dim}', window_history_size={self.window_history_size}, " \
                f"window_lead_time={self.window_lead_time}, overwrite_local_data={self.overwrite_local_data}, " \
-               f"transformation={self.transformation}, **{self.kwargs})"
+               f"transformation={self._print_transformation_as_string}, **{self.kwargs})"
+
+    @property
+    def _print_transformation_as_string(self):
+        str_name = ''
+        if self.transformation is None:
+            str_name = f'{None}'
+        else:
+            for k, v in self.transformation.items():
+                if v is not None:
+                    try:
+                        v_pr = f"xr.DataArray.from_dict({v.to_dict()})"
+                    except AttributeError:
+                        v_pr = f"'{v}'"
+                    str_name += f"'{k}':{v_pr}, "
+            str_name = f"{{{str_name}}}"
+        return str_name
 
     def get_transposed_history(self) -> xr.DataArray:
         """Return history.
@@ -608,6 +624,8 @@ class StationPrep(AbstractStationPrep):
         self.check_inverse_transform_params(self.mean, self.std, self._transform_method)
         self.data, self.mean, self.std = f_inverse(self.data, self.mean, self.std, self._transform_method)
         self._transform_method = None
+        # update X and Y
+        self.make_samples()
 
     def get_transformation_information(self, variable: str = None) -> Tuple[data_or_none, data_or_none, str]:
         """
@@ -641,8 +659,14 @@ if __name__ == "__main__":
                      statistics_per_var=statistics_per_var, station_type='background',
                      network='UBA', sampling='daily', target_dim='variables', target_var='o3',
                      interpolate_dim='datetime', window_history_size=7, window_lead_time=3,
-                     transformation={'method': 'standardise'})
-    sp.set_transformation({'method': 'standardise', 'mean': sp.mean+2, 'std': sp.std+1})
+                     )  # transformation={'method': 'standardise'})
+    # sp.set_transformation({'method': 'standardise', 'mean': sp.mean+2, 'std': sp.std+1})
+    sp2 = StationPrep(data_path='/home/felix/PycharmProjects/mlt_new/data/', station='DEBY122',
+                      statistics_per_var=statistics_per_var, station_type='background',
+                      network='UBA', sampling='daily', target_dim='variables', target_var='o3',
+                      interpolate_dim='datetime', window_history_size=7, window_lead_time=3,
+                      transformation={'method': 'standardise'})
+    sp2.transform(inverse=True)
     sp.get_X()
     sp.get_Y()
     print(len(sp))