minor edit and add test

openeo_processes_dask/process_implementations/cubes/_filter.py

@@ -62,18 +62,10 @@ def filter_temporal(
         # The specified instance in time is excluded from the interval.
         # See https://processes.openeo.org/#filter_temporal
 
-    try:
+        data = data.where(~np.isnat(data[applicable_temporal_dimension]), drop=True)
         filtered = data.loc[
             {applicable_temporal_dimension: slice(start_time, end_time)}
         ]
-    except:
-        try:
-            data = data.where(~np.isnat(data[applicable_temporal_dimension]), drop=True)
-            filtered = data.loc[
-                {applicable_temporal_dimension: slice(start_time, end_time)}
-            ]
-        except Exception as e:
-            raise e
 
     return filtered
 

tests/test_filter.py

@@ -1,6 +1,8 @@
+import copy
 from functools import partial
 
 import numpy as np
+import pandas as pd
 import pytest
 import xarray as xr
 from openeo_pg_parser_networkx.pg_schema import ParameterReference, TemporalInterval
@@ -59,6 +61,11 @@ def test_filter_temporal(temporal_interval, bounding_box, random_raster_data):
         input_cube.loc[dict(t=slice("2018-05-01T00:00:00", "2018-05-02T23:59:59"))],
     )
 
+    new_coords = list(copy.deepcopy(input_cube.coords["t"].data))
+    new_coords[1] = pd.NaT
+    invalid_input_cube = input_cube.assign_coords({"t": np.array(new_coords)})
+    filter_temporal(invalid_input_cube, temporal_interval)
+
 
 @pytest.mark.parametrize("size", [(1, 1, 1, 2)])
 @pytest.mark.parametrize("dtype", [np.uint8])