diff --git a/mlair/data_handler/data_handler_mixed_sampling.py b/mlair/data_handler/data_handler_mixed_sampling.py
index 565a50df51ffbf2ed316b375bcae2588c29b7f50..03f10eb85ec81648585b9bc6b830ad71cc7828a7 100644
--- a/mlair/data_handler/data_handler_mixed_sampling.py
+++ b/mlair/data_handler/data_handler_mixed_sampling.py
@@ -236,7 +236,7 @@ class DataHandlerMixedSamplingWithClimateFirFilterSingleStation(DataHandlerMixed
 
     def _extract_lazy(self, lazy_data):
         _data, _meta, _input_data, _target_data, self.climate_filter_coeff, self.apriori, self.all_apriori = lazy_data
-        DataHandlerSingleStation._extract_lazy(self, (_data, _meta, _input_data, _target_data))
+        DataHandlerMixedSamplingWithFilterSingleStation._extract_lazy(self, (_data, _meta, _input_data, _target_data))
 
     @staticmethod
     def _get_fs(**kwargs):
diff --git a/mlair/helpers/filter.py b/mlair/helpers/filter.py
index ff3bb6a51164dc4f2baebb9fdec40d6902e084d1..9f7b5a6ebcb62b87b9eb059027bab4844fa2e67a 100644
--- a/mlair/helpers/filter.py
+++ b/mlair/helpers/filter.py
@@ -397,13 +397,13 @@ class ClimateFIRFilter:
             #     filt = xr.apply_ufunc(fir_filter_vectorized, filter_input_data, time_axis,
             #                           input_core_dims=[[new_dim], []], output_core_dims=[[new_dim]], vectorize=True,
             #                           kwargs=kwargs)
-            # with TimeTracking(name="convolve"):
-            slicer = slice(int(-(length - 1) / 2), int((length - 1) / 2))
-            filt = xr.apply_ufunc(fir_filter_convolve_vectorized, filter_input_data.sel({new_dim: slicer}),
-                                  input_core_dims=[[new_dim]],
-                                  output_core_dims=[[new_dim]],
-                                  vectorize=True,
-                                  kwargs={"h": h})
+            with TimeTracking(name="convolve"):
+                slicer = slice(int(-(length - 1) / 2), int((length - 1) / 2))
+                filt = xr.apply_ufunc(fir_filter_convolve_vectorized, filter_input_data.sel({new_dim: slicer}),
+                                      input_core_dims=[[new_dim]],
+                                      output_core_dims=[[new_dim]],
+                                      vectorize=True,
+                                      kwargs={"h": h})
 
             # plot
             if self.plot_path is not None: