refac on different lines

mlair/data_handler/data_handler_single_station.py

@@ -223,7 +223,8 @@ class DataHandlerSingleStation(AbstractDataHandler):
             elif method == "centre":
                 return statistics.centre_apply(data, mean), {"mean": mean, "method": method}
             elif method == "min_max":
-                return statistics.min_max_apply(data, min, max), {"min": min, "max": max, "method": method,
+                kws = {"feature_range": feature_range} if feature_range is not None else {}
+                return statistics.min_max_apply(data, min, max, **kws), {"min": min, "max": max, "method": method,
                                                                   "feature_range": feature_range}
             elif method == "log":
                 return statistics.log_apply(data, mean, std), {"mean": mean, "std": std, "method": method}
@@ -416,8 +417,7 @@ class DataHandlerSingleStation(AbstractDataHandler):
         """
         chem_vars = ["benzene", "ch4", "co", "ethane", "no", "no2", "nox", "o3", "ox", "pm1", "pm10", "pm2p5",
                      "propane", "so2", "toluene"]
-        # used_chem_vars = list(set(chem_vars) & set(self.statistics_per_var.keys()))
-        used_chem_vars = list(set(chem_vars) & set(data.variables.values))
+        used_chem_vars = list(set(chem_vars) & set(data.coords[self.target_dim].values))
         if len(used_chem_vars) > 0:
             data.loc[..., used_chem_vars] = data.loc[..., used_chem_vars].clip(min=minimum)
         return data
@@ -463,11 +463,8 @@ class DataHandlerSingleStation(AbstractDataHandler):
         :return: this array
         """
         ind = pd.DataFrame({'val': index_value}, index=index_value)
-        # res = xr.Dataset.from_dataframe(ind).to_array().rename({'index': index_name}).squeeze(dim=squeez/e_dim, drop=True)
         res = xr.Dataset.from_dataframe(ind).to_array(squeeze_dim).rename({'index': index_name}).squeeze(
-            dim=squeeze_dim,
-            drop=True
-        )
+            dim=squeeze_dim, drop=True)
         res.name = index_name
         return res
 
@@ -750,8 +747,6 @@ class DataHandlerSingleStation(AbstractDataHandler):
 
 
 if __name__ == "__main__":
-    # dp = AbstractDataPrep('data/', 'dummy', 'DEBW107', ['o3', 'temp'], statistics_per_var={'o3': 'dma8eu', 'temp': 'maximum'})
-    # print(dp)
     statistics_per_var = {'o3': 'dma8eu', 'temp-rea-miub': 'maximum'}
     sp = DataHandlerSingleStation(data_path='/home/felix/PycharmProjects/mlt_new/data/', station='DEBY122',
                                   statistics_per_var=statistics_per_var, station_type='background',

mlair/helpers/statistics.py

@@ -152,7 +152,10 @@ def min_max_apply(data: Data, _min: Data, _max: Data, feature_range: Data = (0,
     :param feature_range: scale data to any interval given in feature range. Default is scaling on interval [0, 1].
     :return: min/max scaled data
     """
+    if not isinstance(feature_range, xr.DataArray):
         return (data - _min) / (_max - _min) * (max(feature_range) - min(feature_range)) + min(feature_range)
+    else:
+        return (data - _min) / (_max - _min) * (feature_range.max() - feature_range.min()) + feature_range.min()
 
 
 def log(data: Data, dim: Union[str, int]) -> Tuple[Data, Dict[(str, Data)]]: