update aggregate_temporal

openeo_processes_dask/process_implementations/cubes/aggregate.py

@@ -55,6 +55,15 @@ def aggregate_temporal(
                 f"The data cube contains multiple temporal dimensions: {temporal_dims}. The parameter `dimension` must be specified."
             )
         t = temporal_dims[0]
+    if isinstance(intervals, TemporalIntervals) or isinstance(intervals, list):
+        interval_str = []
+        for interval in intervals:
+            if isinstance(interval, TemporalInterval):
+                interval_0 = str(interval[0].root)
+                interval_1 = str(interval[1].root)
+                interval_str.append([interval_0, interval_1])
+        if interval_str:
+            intervals = interval_str
 
     intervals_np = (
         np.array(intervals, dtype=np.datetime64).astype("datetime64[s]").astype(float)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "openeo-processes-dask"
-version = "2024.12.1"
+version = "2025.1.1"
 description = "Python implementations of many OpenEO processes, dask-friendly by default."
 authors = ["Lukas Weidenholzer <[email protected]>", "Sean Hoyal <[email protected]>", "Valentina Hutter <[email protected]>"]
 maintainers = ["EODC Staff <[email protected]>"]

tests/test_aggregate.py

@@ -5,7 +5,11 @@
 import pytest
 import xarray as xr
 import xvec
-from openeo_pg_parser_networkx.pg_schema import ParameterReference, TemporalInterval
+from openeo_pg_parser_networkx.pg_schema import (
+    ParameterReference,
+    TemporalInterval,
+    TemporalIntervals,
+)
 
 from openeo_processes_dask.process_implementations.cubes.aggregate import *
 from openeo_processes_dask.process_implementations.cubes.reduce import reduce_dimension
@@ -27,7 +31,31 @@
             ],
             ["half-1", "half-2"],
             2,
-        )
+        ),
+        (
+            ["2018-01-01T00:00:00", "2019-01-01T00:00:00"],
+            [
+                TemporalInterval.model_validate(
+                    ["2018-01-01T12:00:00", "2018-06-01T12:00:00"]
+                ),
+                TemporalInterval.model_validate(
+                    ["2018-07-01T12:00:00", "2018-12-01T12:00:00"]
+                ),
+            ],
+            ["half-1", "half-2"],
+            2,
+        ),
+        (
+            ["2018-01-01T00:00:00", "2019-01-01T00:00:00"],
+            TemporalIntervals.model_validate(
+                [
+                    ["2018-01-01T12:00:00", "2018-06-01T12:00:00"],
+                    ["2018-07-01T12:00:00", "2018-12-01T12:00:00"],
+                ]
+            ),
+            ["half-1", "half-2"],
+            2,
+        ),
     ],
 )
 def test_aggregate_temporal(
@@ -43,7 +71,7 @@ def test_aggregate_temporal(
     input_cube = create_fake_rastercube(
         data=random_raster_data,
         spatial_extent=bounding_box,
-        temporal_extent=TemporalInterval.parse_obj(temporal_extent),
+        temporal_extent=TemporalInterval.model_validate(temporal_extent),
         bands=["B02", "B03", "B04", "B08"],
     )