maybe found axis bug

mlair/helpers/filter.py

@@ -267,11 +267,11 @@ class ClimateFIRFilter:
         kwargs = {"fs": fs, "cutoff_high": cutoff_high, "order": order,
                   "causal": False, "padlen": int(min(padlen_factor, 1) * length)}
         with TimeTracking():
-            filt = fir_filter_numpy_vectorized(filter_input_data, var_dim, kwargs)
-        with TimeTracking():
-            filt = xr.apply_ufunc(fir_filter_vectorized, filter_input_data, time_axis,
-                                  input_core_dims=[[new_dim], []], output_core_dims=[[new_dim]], vectorize=True,
-                                  kwargs=kwargs)
+            filt = fir_filter_numpy_vectorized(filter_input_data, var_dim, new_dim, kwargs)
+        # with TimeTracking():
+        #     filt = xr.apply_ufunc(fir_filter_vectorized, filter_input_data, time_axis,
+        #                           input_core_dims=[[new_dim], []], output_core_dims=[[new_dim]], vectorize=True,
+        #                           kwargs=kwargs)
 
         # plot
         if self.plot_path is not None:
@@ -393,12 +393,13 @@ def fir_filter(data, fs, order=5, cutoff_low=None, cutoff_high=None, window="ham
     return filtered, h
 
 
-def fir_filter_numpy_vectorized(filter_input_data, var_dim, kwargs):
+def fir_filter_numpy_vectorized(filter_input_data, var_dim, new_dim, kwargs):
     filt_np = xr.DataArray(np.nan, coords=filter_input_data.coords)
     for var in filter_input_data.coords[var_dim]:
         logging.info(
             f"{filter_input_data.coords['Stations'].values[0]}: {str(var.values)}")  # ToDo must be removed, just for debug
-        a = da.apply_along_axis(fir_filter_vectorized, 2, filter_input_data.sel({var_dim: var}).values, **kwargs)
+        a = np.apply_along_axis(fir_filter_vectorized, filter_input_data.dims.index(new_dim),
+                                filter_input_data.sel({var_dim: var}).values, **kwargs)
         filt_np.loc[{var_dim: var}] = a
     return filt_np