diff --git a/src/helpers.py b/src/helpers.py
index be73614319b39dc36043437c64379342a96ce00e..dc5e3741af0e296fbe2021efc675729eacc12e73 100644
--- a/src/helpers.py
+++ b/src/helpers.py
@@ -11,6 +11,8 @@ import math
 import os
 import socket
 import time
+import types
+
 
 import keras.backend as K
 import xarray as xr
@@ -53,6 +55,9 @@ class TimeTrackingWrapper:
         with TimeTracking(name=self.__wrapped__.__name__):
             return self.__wrapped__(*args, **kwargs)
 
+    def __get__(self, instance, cls):
+        return types.MethodType(self, instance)
+
 
 class TimeTracking(object):
     """
@@ -115,6 +120,7 @@ def prepare_host(create_new=True, sampling="daily"):
     except OSError:
         user = "default"
     if hostname == "ZAM144":
+        user = "felix"
         path = f"/home/{user}/Data/toar_{sampling}/"
     elif hostname == "zam347":
         path = f"/home/{user}/Data/toar_{sampling}/"
diff --git a/src/plotting/postprocessing_plotting.py b/src/plotting/postprocessing_plotting.py
index c0e2b1ed063bb67d079cd184a574360070e61424..51286405ff53ff78dd0414567468ff3dd83cee0d 100644
--- a/src/plotting/postprocessing_plotting.py
+++ b/src/plotting/postprocessing_plotting.py
@@ -347,6 +347,8 @@ class PlotConditionalQuantiles(AbstractPlotClass):
 
         :return:
         """
+        logging.info(f"start plotting {self.__name__}, scheduled number of plots: {(len(self.seasons) + 1) * 2}")
+
         if len(self.seasons) > 0:
             self._plot_seasons()
         self._plot_all()
@@ -372,7 +374,7 @@ class PlotConditionalQuantiles(AbstractPlotClass):
         self._plot_base(data=self._data, x_model=self._model_name, y_model=self._obs_name, plot_name_affix="cali-ref")
         self._plot_base(data=self._data, x_model=self._obs_name, y_model=self._model_name, plot_name_affix="like-base")
 
-    # @TimeTrackingWrapper
+    @TimeTrackingWrapper
     def _plot_base(self, data, x_model, y_model, plot_name_affix, season=""):
         """
         Base method to create cond. quantile plots. Is called from _plot_all and _plot_seasonal
@@ -384,6 +386,7 @@ class PlotConditionalQuantiles(AbstractPlotClass):
         :param season: List of seasons to use
         :return:
         """
+
         segmented_data, quantile_panel = self._prepare_plots(data, x_model, y_model)
         ylabel, xlabel = self._labels(x_model, self._opts["data_unit"])
         plot_name = f"{self.plot_name}{self.add_affix(season)}{self.add_affix(plot_name_affix)}_plot.pdf"