min_periods defaults to 1

xarray/core/dataarray.py

@@ -6935,7 +6935,7 @@ def rolling(
     def cumulative(
         self,
         dim: str | Iterable[Hashable],
-        min_periods: int | None = 1,
+        min_periods: int = 1,
     ) -> DataArrayRolling:
         """
         Accumulating object for DataArrays.
@@ -6944,7 +6944,7 @@ def cumulative(
         ----------
         dims : iterable of hashable
             The name(s) of the dimensions to create the cumulative window along
-        min_periods : int or None, default: None
+        min_periods : int, default: 1
             Minimum number of observations in window required to have a value
             (otherwise result is NA). The default is 1 (note this is different
             from ``Rolling``, whose default is the size of the window).
@@ -7005,7 +7005,7 @@ def cumulative(
                 )
             dim = {d: self.sizes[d] for d in dim}
 
-        return DataArrayRolling(self, dim, min_periods=min_periods or 1, center=False)
+        return DataArrayRolling(self, dim, min_periods=min_periods, center=False)
 
     def coarsen(
         self,

xarray/core/dataset.py

@@ -10381,7 +10381,7 @@ def rolling(
     def cumulative(
         self,
         dim: str | Iterable[Hashable],
-        min_periods: int | None = 1,
+        min_periods: int = 1,
     ) -> DatasetRolling:
         """
         Accumulating object for Datasets
@@ -10390,7 +10390,7 @@ def cumulative(
         ----------
         dims : iterable of hashable
             The name(s) of the dimensions to create the cumulative window along
-        min_periods : int or None, default: None
+        min_periods : int, default: 1
             Minimum number of observations in window required to have a value
             (otherwise result is NA). The default is 1 (note this is different
             from ``Rolling``, whose default is the size of the window).
@@ -10421,7 +10421,7 @@ def cumulative(
                 )
             dim = {d: self.sizes[d] for d in dim}
 
-        return DatasetRolling(self, dim, min_periods=min_periods or 1, center=False)
+        return DatasetRolling(self, dim, min_periods=min_periods, center=False)
 
     def coarsen(
         self,

xarray/tests/test_rolling.py

@@ -486,23 +486,28 @@ def test_rolling_exp_keep_attrs(self, da, func) -> None:
             da.rolling_exp(time=10, keep_attrs=True)
 
     @pytest.mark.parametrize("func", ["mean", "sum"])
-    @pytest.mark.parametrize("min_periods", [None, 1, 20])
+    @pytest.mark.parametrize("min_periods", [1, 20])
     def test_cumulative(self, da, func, min_periods) -> None:
         # One dim
         result = getattr(da.cumulative("time", min_periods=min_periods), func)()
         expected = getattr(
-            da.rolling(time=da.time.size, min_periods=min_periods or 1), func
+            da.rolling(time=da.time.size, min_periods=min_periods), func
         )()
         assert_identical(result, expected)
 
         # Multiple dim
         result = getattr(da.cumulative(["time", "a"], min_periods=min_periods), func)()
         expected = getattr(
-            da.rolling(time=da.time.size, a=da.a.size, min_periods=min_periods or 1),
+            da.rolling(time=da.time.size, a=da.a.size, min_periods=min_periods),
             func,
         )()
         assert_identical(result, expected)
 
+    def test_cumulative_vs_cum(self, da) -> None:
+        result = da.cumulative("time").sum()
+        expected = da.cumsum("time")
+        assert_identical(result, expected)
+
 
 class TestDatasetRolling:
     @pytest.mark.parametrize(
@@ -829,19 +834,19 @@ def test_raise_no_warning_dask_rolling_assert_close(self, ds, name) -> None:
 
     @pytest.mark.parametrize("func", ["mean", "sum"])
     @pytest.mark.parametrize("ds", (2,), indirect=True)
-    @pytest.mark.parametrize("min_periods", [None, 1, 10])
+    @pytest.mark.parametrize("min_periods", [1, 10])
     def test_cumulative(self, ds, func, min_periods) -> None:
         # One dim
         result = getattr(ds.cumulative("time", min_periods=min_periods), func)()
         expected = getattr(
-            ds.rolling(time=ds.time.size, min_periods=min_periods or 1), func
+            ds.rolling(time=ds.time.size, min_periods=min_periods), func
         )()
         assert_identical(result, expected)
 
         # Multiple dim
         result = getattr(ds.cumulative(["time", "x"], min_periods=min_periods), func)()
         expected = getattr(
-            ds.rolling(time=ds.time.size, x=ds.x.size, min_periods=min_periods or 1),
+            ds.rolling(time=ds.time.size, x=ds.x.size, min_periods=min_periods),
             func,
         )()
         assert_identical(result, expected)