Write chunks with negative zero values and a zero fill value

changes/3144.bugfix.rst

@@ -0,0 +1 @@
+Ensure that -0.0 is not considered equal to 0.0 when checking if all the values in a chunk are equal to an array's fill value.```

src/zarr/core/buffer/core.py

@@ -523,6 +523,15 @@ def all_equal(self, other: Any, equal_nan: bool = True) -> bool:
         if other is None:
             # Handle None fill_value for Zarr V2
             return False
+        # Handle positive and negative zero by comparing bit patterns:
+        if (
+            np.asarray(other).dtype.kind == "f"
+            and other == 0.0
+            and self._data.dtype.kind not in ("U", "S", "T", "O", "V")
+        ):
+            _data, other = np.broadcast_arrays(self._data, np.asarray(other, self._data.dtype))
+            void_dtype = "V" + str(_data.dtype.itemsize)
+            return np.array_equal(_data.view(void_dtype), other.view(void_dtype))
         # use array_equal to obtain equal_nan=True functionality
         # Since fill-value is a scalar, isn't there a faster path than allocating a new array for fill value
         # every single time we have to write data?

tests/test_array.py

@@ -870,6 +870,30 @@ def test_write_empty_chunks_behavior(
         assert arr.nchunks_initialized == arr.nchunks
 
 
+@pytest.mark.parametrize("store", ["memory"], indirect=True)
+@pytest.mark.parametrize("fill_value", [0.0, -0.0])
+@pytest.mark.parametrize("dtype", ["f4", "f2"])
+def test_write_empty_chunks_negative_zero(
+    zarr_format: ZarrFormat, store: MemoryStore, fill_value: float, dtype: str
+) -> None:
+    # regression test for https://github.com/zarr-developers/zarr-python/issues/3144
+
+    arr = zarr.create_array(
+        store=store,
+        shape=(2,),
+        zarr_format=zarr_format,
+        dtype=dtype,
+        fill_value=fill_value,
+        chunks=(1,),
+        config={"write_empty_chunks": False},
+    )
+    assert arr.nchunks_initialized == 0
+
+    # initialize the with the negated fill value (-0.0 for +0.0, +0.0 for -0.0)
+    arr[:] = -fill_value
+    assert arr.nchunks_initialized == arr.nchunks
+
+
 @pytest.mark.parametrize(
     ("fill_value", "expected"),
     [