(chore): clean up offsets creation

src/anndata/_core/sparse_dataset.py

@@ -269,28 +269,23 @@ def get_compressed_vectors_for_slices(
     x: BackedSparseMatrix, slices: Iterable[slice]
 ) -> tuple[Sequence, Sequence, Sequence]:
     indptr_indices = [x.indptr[slice(s.start, s.stop + 1)] for s in slices]
-    indptr_limits = [(i[0], i[-1]) for i in indptr_indices]
+    indptr_limits = [slice(i[0], i[-1]) for i in indptr_indices]
     # HDF5 cannot handle out-of-order integer indexing
     if isinstance(x.data, ZarrArray):
-        indptr_int = np.concatenate(
-            [np.arange(start, stop) for start, stop in indptr_limits]
-        )
+        indptr_int = np.concatenate([np.arange(s.start, s.stop) for s in indptr_limits])
         data = x.data[indptr_int]
         indices = x.indices[indptr_int]
     else:
-        data = np.concatenate([x.data[start:stop] for start, stop in indptr_limits])
-        indices = np.concatenate(
-            [x.indices[start:stop] for start, stop in indptr_limits]
-        )
+        data = np.concatenate([x.data[s] for s in indptr_limits])
+        indices = np.concatenate([x.indices[s] for s in indptr_limits])
     # Need to track the size of the gaps in the slices to each indptr subselection
-    offsets = [indptr_indices[0][0]]
-    for (_, stop0), (start1, _) in pairwise(indptr_limits):
-        offsets.append((start1 - stop0) + offsets[-1])
-    start_indptr = indptr_indices[0] - offsets[0]
+    gaps = (s1.start - s0.stop for s0, s1 in pairwise(indptr_limits))
+    offsets = accumulate(chain([indptr_limits[0].start], gaps))
+    start_indptr = indptr_indices[0] - next(offsets)
     if len(slices) < 2:  # there is only one slice so no need to concatenate
         return data, indices, start_indptr
     end_indptr = np.concatenate(
-        [s[1:] - offsets[i + 1] for i, s in enumerate(indptr_indices[1:])]
+        [s[1:] - o for s, o in zip(indptr_indices[1:], offsets)]
     )
     indptr = np.concatenate([start_indptr, end_indptr])
     return data, indices, indptr