kz filter data handler can also handle new schemes

mlair/data_handler/data_handler_kz_filter.py

@@ -32,7 +32,6 @@ class DataHandlerKzFilterSingleStation(DataHandlerSingleStation):
         self.kz_filter_iter = kz_filter_iter
         self.cutoff_period = None
         self.cutoff_period_days = None
-        self.data_target: xr.DataArray = None
         super().__init__(*args, **kwargs)
 
     def setup_samples(self):
@@ -41,26 +40,25 @@ class DataHandlerKzFilterSingleStation(DataHandlerSingleStation):
         """
         self.load_data()
         self.interpolate(dim=self.time_dim, method=self.interpolation_method, limit=self.interpolation_limit)
+        self.set_inputs_and_targets()
         import matplotlib
         matplotlib.use("TkAgg")
         import matplotlib.pyplot as plt
-        # self.original_data = self.data  # ToDo: implement here something to store unfiltered data
         self.apply_kz_filter()
         # self.data.sel(filter="74d", variables="temp", Stations="DEBW107").plot()
         # self.data.sel(variables="temp", Stations="DEBW107").plot.line(hue="filter")
-        if self.transformation is not None:
+        if self.do_transformation is True:
             self.call_transform()
-        self.make_samples()  # ToDo: target samples are still coming from filtered data
+        self.make_samples()
 
     @TimeTrackingWrapper
     def apply_kz_filter(self):
         """Apply kolmogorov zurbenko filter only on inputs."""
-        self.data_target = self.data.sel({self.target_dim: [self.target_var]})
-        kz = KZFilter(self.data, wl=self.kz_filter_length, itr=self.kz_filter_iter, filter_dim="datetime")
+        kz = KZFilter(self.input_data.data, wl=self.kz_filter_length, itr=self.kz_filter_iter, filter_dim="datetime")
         filtered_data: List[xr.DataArray] = kz.run()
         self.cutoff_period = kz.period_null()
         self.cutoff_period_days = kz.period_null_days()
-        self.data = xr.concat(filtered_data, pd.Index(self.create_filter_index(), name="filter"))
+        self.input_data.data = xr.concat(filtered_data, pd.Index(self.create_filter_index(), name="filter"))
 
     def create_filter_index(self) -> pd.Index:
         """
@@ -75,36 +73,6 @@ class DataHandlerKzFilterSingleStation(DataHandlerSingleStation):
         index = list(map(lambda x: str(x) + "d", index)) + ["res"]
         return pd.Index(index, name="filter")
 
-    def make_labels(self, dim_name_of_target: str, target_var: str_or_list, dim_name_of_shift: str,
-                    window: int) -> None:
-        """
-        Create a xr.DataArray containing labels.
-
-        Labels are defined as the consecutive target values (t+1, ...t+n) following the current time step t. Set label
-        attribute.
-
-        :param dim_name_of_target: Name of dimension which contains the target variable
-        :param target_var: Name of target variable in 'dimension'
-        :param dim_name_of_shift: Name of dimension on which xarray.DataArray.shift will be applied
-        :param window: lead time of label
-        """
-        window = abs(window)
-        data = self.data_target.sel({dim_name_of_target: target_var})
-        self.label = self.shift(data, dim_name_of_shift, window)
-
-    def make_observation(self, dim_name_of_target: str, target_var: str_or_list, dim_name_of_shift: str) -> None:
-        """
-        Create a xr.DataArray containing observations.
-
-        Observations are defined as value of the current time step t. Set observation attribute.
-
-        :param dim_name_of_target: Name of dimension which contains the observation variable
-        :param target_var: Name of observation variable(s) in 'dimension'
-        :param dim_name_of_shift: Name of dimension on which xarray.DataArray.shift will be applied
-        """
-        data = self.data_target.sel({dim_name_of_target: target_var})
-        self.observation = self.shift(data, dim_name_of_shift, 0)
-
     def get_transposed_history(self) -> xr.DataArray:
         """Return history.
 

mlair/data_handler/data_handler_single_station.py

@@ -144,7 +144,7 @@ class DataHandlerSingleStation(AbstractDataHandler):
         self.load_data()
         self.interpolate(dim=self.time_dim, method=self.interpolation_method, limit=self.interpolation_limit)
         self.set_inputs_and_targets()
-        if self.do_transformation:
+        if self.do_transformation is True:
             self.call_transform()
         self.make_samples()