Add setitem tests and resolve comments

Author: lshaw8317

src/blosc2/lazyexpr.py

@@ -46,67 +46,6 @@
     import numexpr
 
 
-# No longer used
-# def compute_slice_shape(shape, slice_obj, dont_squeeze=False):
-#     # Handle None or empty slice case
-#     if slice_obj is None or slice_obj == ():
-#         return shape
-
-#     # Use ndindex to handle slice calculations
-#     try:
-#         idx = ndindex.ndindex(slice_obj).expand(shape)
-#         return idx.shape
-#     except Exception:
-#         # Fall back to manual processing
-#         if not isinstance(slice_obj, tuple):
-#             slice_obj = (slice_obj,)
-
-#         result = []
-#         shape_idx = 0
-#         dims_reduced = 0
-
-#         # Process slice components
-#         for i, s in enumerate(slice_obj):
-#             if i >= len(shape):
-#                 break
-
-#             if isinstance(s, slice):
-#                 start = 0 if s.start is None else max(0, s.start if s.start >= 0 else shape[i] + s.start)
-#                 stop = (
-#                     shape[i]
-#                     if s.stop is None
-#                     else min(shape[i], s.stop if s.stop >= 0 else shape[i] + s.stop)
-#                 )
-#                 step = 1 if s.step is None else abs(s.step)
-
-#                 if start < stop:
-#                     result.append((stop - start - 1) // step + 1)
-#                 else:
-#                     result.append(0)
-#                 shape_idx += 1
-#             elif isinstance(s, int) or np.isscalar(s):
-#                 if dont_squeeze:
-#                     result.append(1)
-#                     shape_idx += 1
-#                 else:
-#                     # Integer indexing reduces dimensionality
-#                     dims_reduced += 1
-#                     shape_idx += 1
-#                     continue
-#             elif s is Ellipsis:
-#                 # Fill in with remaining dimensions
-#                 remaining_dims = len(shape) - (len(slice_obj) - 1 + dims_reduced)
-#                 result.extend(shape[shape_idx : shape_idx + remaining_dims])
-#                 shape_idx += remaining_dims
-#                 continue
-
-#         # Add any remaining dimensions
-#         if shape_idx < len(shape):
-#             result.extend(shape[shape_idx:])
-
-#         return tuple(result)
-
-
 def ne_evaluate(expression, local_dict=None, **kwargs):
     """Safely evaluate expressions using numexpr when possible, falling back to numpy."""
     if local_dict is None:

src/blosc2/ndarray.py

@@ -1020,47 +1020,6 @@ def __setitem__(self, key, value):
         super().__setitem__(key, value)
 
 
-# No longer used
-# def extract_values(arr, indices: np.ndarray[np.int_], max_cache_size: int = 10) -> np.ndarray:
-#     """
-#     Extract values from a chunked and compressed array using an array of indices.
-
-#     Parameters
-#     ----------
-#     arr : blosc2.NDArray
-#         The chunked and compressed array.
-#     indices : np.ndarray
-#         The array of indices to extract values from.
-#     max_cache_size : int
-#         The maximum number of chunks to cache.
-
-#     Returns
-#     -------
-#     extracted_values : np.ndarray
-#         The extracted values.
-#     """
-#     # Initialize the result array
-#     extracted_values = np.empty(len(indices), dtype=arr.dtype)
-
-#     # Limited size dictionary to store decompressed chunks
-#     chunk_cache = LimitedSizeDict(max_cache_size)
-
-#     # Iterate through the indices and extract values
-#     chunk_size = int(arr.chunks[0])
-#     for i, idx in enumerate(indices):
-#         chunk_idx = idx // chunk_size
-#         if chunk_idx not in chunk_cache:
-#             # Compute the bounds for this chunk
-#             start = chunk_idx * chunk_size
-#             end = start + chunk_size
-#             chunk_cache[chunk_idx] = arr[start:end]
-
-#         local_idx = idx % chunk_size
-#         extracted_values[i] = chunk_cache[chunk_idx][local_idx]
-
-#     return extracted_values
-
-
 def detect_aligned_chunks(  # noqa: C901
     key: Sequence[slice], shape: Sequence[int], chunks: Sequence[int], consecutive: bool = False
 ) -> list[int]:

tests/array-api-xfails.txt

@@ -1,3 +1,2 @@
-array_api_tests/test_array_object.py::test_getitem
 array_api_tests/test_array_object.py::test_setitem
 array_api_tests/test_array_object.py::test_getitem_masking

tests/ndarray/test_setitem.py

@@ -19,6 +19,7 @@
     ([12, 13, 14, 15, 16], [5, 5, 5, 5, 5], [2, 2, 2, 2, 2], (slice(1, 9, 2), ..., slice(3, 6)), np.float32),
     ([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),
 ]