Raise if seasons are not sorted for resampling

pydata · dcherian · May 7, 2025 · Jun 28, 2024 · Sep 20, 2024 · Sep 22, 2024
commit be5f9337fede955ab8cbc9fdaeb077e3cb643549
diff --git a/xarray/groupers.py b/xarray/groupers.py
@@ -598,6 +598,32 @@ def inds_to_string(asints: tuple[tuple[int, ...], ...]) -> tuple[str, ...]:
     return tuple("".join([inits[i_ - 1] for i_ in t]) for t in asints)
 
 
+def is_sorted_periodic(lst):
+    n = len(lst)
+
+    # Find the wraparound point where the list decreases
+    wrap_point = -1
+    for i in range(1, n):
+        if lst[i] < lst[i - 1]:
+            wrap_point = i
+            break
+
+    # If no wraparound point is found, the list is already sorted
+    if wrap_point == -1:
+        return True
+
+    # Check if both parts around the wrap point are sorted
+    for i in range(1, wrap_point):
+        if lst[i] < lst[i - 1]:
+            return False
+    for i in range(wrap_point + 1, n):
+        if lst[i] < lst[i - 1]:
+            return False
+
+    # Check wraparound condition
+    return lst[-1] <= lst[0]
+
+
 @dataclass
 class SeasonsGroup:
     seasons: tuple[str, ...]
@@ -749,6 +775,12 @@ def __post_init__(self):
             )
         self.season_tuples = dict(zip(self.seasons, self.season_inds, strict=True))
 
+        if not is_sorted_periodic(list(itertools.chain(*self.season_inds))):
+            raise ValueError(
+                "Resampling is only supported with sorted seasons. "
+                f"Provided seasons {self.seasons!r} are not sorted."
+            )
+
     def factorize(self, group: T_Group) -> EncodedGroups:
         if group.ndim != 1:
             raise ValueError(

diff --git a/xarray/tests/test_groupby.py b/xarray/tests/test_groupby.py
@@ -3174,6 +3174,14 @@ def test_season_grouper_simple(self, calendar) -> None:
         ).mean()
         assert_identical(expected, actual)
 
+    @pytest.mark.parametrize("seasons", [["JJA", "MAM", "SON", "DJF"]])
+    def test_season_resampling_raises_unsorted_seasons(self, seasons):
+        calendar = "standard"
+        time = date_range("2001-01-01", "2002-12-30", freq="D", calendar=calendar)
+        da = DataArray(np.ones(time.size), dims="time", coords={"time": time})
+        with pytest.raises(ValueError, match="sort"):
+            da.resample(time=SeasonResampler(seasons))
+
     # TODO: drop_incomplete
     @requires_cftime
     @pytest.mark.parametrize("drop_incomplete", [True, False])
@@ -3186,7 +3194,6 @@ def test_season_grouper_simple(self, calendar) -> None:
             pytest.param(["DJF", "MAM", "JJA", "ON"], id="skip-september"),
             pytest.param(["JJAS"], id="jjas-only"),
             pytest.param(["MAM", "JJA", "SON", "DJF"], id="different-order"),
-            pytest.param(["JJA", "MAM", "SON", "DJF"], id="out-of-order"),
         ],
     )
     def test_season_resampler(self, seasons: list[str], drop_incomplete: bool) -> None: