reduce all unnecessary dimensions in plot data set to fix error

mlair/plotting/postprocessing_plotting.py

@@ -1252,6 +1252,7 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
                 station_data_x = station.get_X(as_numpy=False)[0]
                 station_data_x = station_data_x.loc[{self.history_dim: 0,  # select recent window frame
                                                      self.target_dim: station_data_x[self.target_dim].values[0]}]
+                station_data_x = self._reduce_dims(station_data_x)
                 avail_list.append(station_data_x.notnull())
             avail_data = xr.concat(avail_list, dim=self.station_dim).notnull()
             avail_data_time_sum[subset] = avail_data.sum(dim=self.station_dim)
@@ -1268,6 +1269,14 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
         self.avail_data_amount = avail_data_amount.reindex({self.temporal_dim: full_time_index})
         self.dataset_time_interval = dataset_time_interval
 
+    def _reduce_dims(self, dataset):
+        if len(dataset.dims) > 2:
+            required = {self.temporal_dim, self.station_dim}
+            unimportant = set(dataset.dims).difference(required)
+            sel_dict = {un: dataset[un].values[0] for un in unimportant}
+            dataset = dataset.loc[sel_dict]
+        return dataset
+
     @staticmethod
     def _get_first_and_last_indexelement_from_xarray(xarray, dim_name, return_type='as_tuple'):
         if isinstance(xarray, xr.DataArray):

mlair/run_modules/pre_processing.py

@@ -121,6 +121,7 @@ class PreProcessing(RunEnvironment):
         self.save_to_tex(path=path, filename="station_sample_size.tex", column_format=column_format, df=df)
         self.save_to_md(path=path, filename="station_sample_size.md", df=df)
         df_nometa = df.drop(meta_data, axis=1)
+        column_format = self.create_column_format_for_tex(df)
         self.save_to_tex(path=path, filename="station_sample_size_short.tex", column_format=column_format, df=df_nometa)
         self.save_to_md(path=path, filename="station_sample_size_short.md", df=df_nometa)
         # df_nometa.to_latex(os.path.join(path, "station_sample_size_short.tex"), na_rep='---',