diff --git a/mlair/plotting/data_insight_plotting.py b/mlair/plotting/data_insight_plotting.py
index 3bec759076a862d89be6c7495ef9abdebd0d4123..4395d1574e42e01ced1b11603445ebee28c16b9b 100644
--- a/mlair/plotting/data_insight_plotting.py
+++ b/mlair/plotting/data_insight_plotting.py
@@ -963,10 +963,13 @@ class PlotClimateFirFilter(AbstractPlotClass):
     def _plot(self, plot_dict, sampling, new_dim="window"):
         td_type = {"1d": "D", "1H": "h"}.get(sampling)
         for var, viz_date_dict in plot_dict.items():
+            print(var)  # TODO remove
             for it0, t0 in enumerate(viz_date_dict.keys()):
+                print(it0)  # TODO remove
                 viz_data = viz_date_dict[t0]
                 residuum_true = None
                 for ifilter in sorted(viz_data.keys()):
+                    print(ifilter)  # TODO remove
                     data = viz_data[ifilter]
                     filter_input = data["filter_input"]
                     filter_input_nc = data["filter_input_nc"] if residuum_true is None else residuum_true.sel(
@@ -978,20 +981,27 @@ class PlotClimateFirFilter(AbstractPlotClass):
                     fig, ax = plt.subplots()
 
                     # plot backgrounds
+
+                    print("plot_valid_area")  # TODO remove
                     self._plot_valid_area(ax, t0, valid_range, td_type)
+                    print("plot_t0")  # TODO remove
                     self._plot_t0(ax, t0)
 
                     # original data
+                    print("plot_original_data")  # TODO remove
                     self._plot_original_data(ax, time_axis, filter_input_nc)
 
                     # clim apriori
+                    print("plot_apriori")  # TODO remove
                     self._plot_apriori(ax, time_axis, filter_input, new_dim, ifilter)
 
                     # clim filter response
+                    print("plot_clim_filter")  # TODO remove
                     residuum_estimated = self._plot_clim_filter(ax, time_axis, filter_input, new_dim, h,
                                                                 output_dtypes=filter_input.dtype)
 
                     # ideal filter response
+                    print("plot_ideal_filter")  # TODO remove
                     residuum_true = self._plot_ideal_filter(ax, time_axis, filter_input_nc, new_dim, h,
                                                             output_dtypes=filter_input.dtype)