Further fixes for setitem

Author: lshaw8317

src/blosc2/core.py

@@ -1467,7 +1467,7 @@ def compute_chunks_blocks(  # noqa: C901
 
     # Return an arbitrary value for chunks and blocks when shape has any 0 dim
     if 0 in shape:
-        return (1,) * len(shape), (1,) * len(shape)
+        return shape, shape
 
     if blocks:
         if not isinstance(blocks, tuple | list):

src/blosc2/lazyexpr.py

@@ -2882,7 +2882,7 @@ def sort(self, order: str | list[str] | None = None) -> blosc2.LazyArray:
             lazy_expr._order = order
         return lazy_expr
 
-    def compute(self, item=(), **kwargs) -> blosc2.NDArray:
+    def compute(self, item=(), **kwargs) -> blosc2.NDArray:  # noqa : C901
         # When NumPy ufuncs are called, the user may add an `out` parameter to kwargs
         if "out" in kwargs:
             kwargs["_output"] = kwargs.pop("out")
@@ -2899,7 +2899,15 @@ def compute(self, item=(), **kwargs) -> blosc2.NDArray:
             kwargs["_indices"] = self._indices
         if hasattr(self, "_order"):
             kwargs["_order"] = self._order
-        result = self._compute_expr(item, kwargs)
+        # handle empty arrays
+        if 0 in self.shape:
+            result = (
+                np.empty(self.shape, dtype=self.dtype)
+                if "_getitem" in kwargs
+                else blosc2.empty(self.shape, dtype=self.dtype)
+            )
+        else:
+            result = self._compute_expr(item, kwargs)
         if "_order" in kwargs and "_indices" not in kwargs:
             # We still need to apply the index in result
             x = self._where_args["_where_x"]

src/blosc2/ndarray.py

@@ -1783,10 +1783,7 @@ def __setitem__(  # noqa : C901
             intersecting_chunks = [
                 slice_to_chunktuple(s, c) for s, c in zip(_slice, chunks, strict=True)
             ]  # internally handles negative steps
-            intersecting_chunks = [
-                (0,) if i == () else i for i in intersecting_chunks
-            ]  # special case of dims with 0 length
-            if isinstance(value, int | float | bool):  # overwrite updater function for simple cases (faster)
+            if np.isscalar(value):  # overwrite updater function for simple cases (faster)
 
                 def updater(sel_idx):
                     return value
@@ -1795,6 +1792,7 @@ def updater(sel_idx):
                 def updater(sel_idx):
                     return value[sel_idx]
 
+            out = self  # for when shape has 0 (i.e. arr is empty, as then skip loop)
             for c in product(*intersecting_chunks):
                 sel_idx, glob_selection, sub_idx = _get_selection(c, _slice, chunks)
                 sel_idx = tuple(s for s, m in zip(sel_idx, mask, strict=True) if not m)
@@ -1813,7 +1811,7 @@ def updater(sel_idx):
             return out
 
         shape = [sp - st for sp, st in zip(stop, start, strict=False)]
-        if isinstance(value, int | float | bool):
+        if np.isscalar(value):
             value = np.full(shape, value, dtype=self.dtype)
         elif isinstance(value, np.ndarray):  # handles decompressed NDArray too
             if value.dtype != self.dtype:

tests/ndarray/test_setitem.py

@@ -20,6 +20,7 @@
     ([12, 13], [5, 5], [2, 2], (slice(11, 2, -1), slice(6, 2, -1)), np.float32),
     ([25, 13, 22], [5, 5, 3], [2, 2, 1], (slice(17, 2, -3), 0, slice(6, 2, -1)), np.float32),
     ([25, 13, 22], [5, 5, 3], [2, 2, 1], (np.s_[-5:-15:-1], np.s_[-3:-11:-2], slice(6, 2, -1)), np.float32),
+    ([0, 13, 22], [0, 5, 3], [0, 2, 1], (np.s_[:], np.s_[-5:-15:-1], slice(6, 2, -1)), np.float32),
 ]