fix(sharding): flatten any multi-dim value for coordinate selections in partial writes - #320

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

…in partial writes (zarr-developers#4316)

* fix(sharding): flatten any multi-dim value for coordinate selections in partial writes

The guard added in zarr-developers#4284 only reshaped the value when its shape equalled
the re-derived CoordinateIndexer's sel_shape. An orthogonal selection that
mixes an integer index with two or more array indices defeats that:
OrthogonalIndexer drops the integer axis from the value but np.ix_ keeps
it as a length-1 axis in the chunk selection, so the shapes differ in rank
while agreeing in element count, the reshape was skipped, and the write
still raised the shape-mismatch ValueError.

The invariant is that a coordinate indexer addresses the value flat, so
ravel any multi-dimensional value instead. Both partial-encode paths now
share one helper for deriving the shard indexer and shaping the value, and
the check is an isinstance on CoordinateIndexer so mypy types sel_shape.

The regression test is parametrized over selections with an integer axis
in each position, three array axes, and an unsorted selection spanning two
shards.

Closes zarr-developers#4315

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

* docs: add changelog entry for #320

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

* Rename 320.bugfix.md to 4316.bugfix.md

* fix(sharding): ravel only a value shaped like the selection minus its unit axes

Ravelling every multi-dimensional value for a coordinate selection was too
lenient. A mask write with a (2, 2) value for four selected elements, or an
orthogonal write with a spurious trailing axis, raises on an unsharded array
but was silently accepted on a sharded one, because the element count
matched and the shard-level selection cannot tell orthogonal from mask
indexing.

The value shape can. An np.ix_ selection has an N-D sel_shape and the
caller's value is that shape minus the integer-indexed axes, which np.ix_
keeps as length-1 axes. Ravel exactly that shape and leave any other rank
alone, so an invalid write fails the same way it does without sharding.

Adds an error test for both leniencies and a positive case with a length-1
array axis next to an integer axis.

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

* test: exercise sharded writes and bare integer axes in the indexing property tests

The property tests could not have found the sharded orthogonal-write bugs:

- test_oindex, test_mask_indexing and test_block_indexing skipped their set
  half on sharded arrays with assume(zarray.shards is None), added in zarr-developers#2825
  when the bug was first seen and never lifted. test_vindex had its set half
  commented out.
- orthogonal_indices wrapped every bare integer as a one-element array, so
  zarr never received an integer index and OrthogonalIndexer's dropped-axis
  path was unreachable. basic_indices(min_dims=1) never yields an integer
  either, so that branch was dead.
- arrays() only drew a shard shape when every axis had a chunk strictly
  between 1 and the axis length, on top of the v3 and regular-grid draws:
  2 of 500 test_oindex examples were sharded.

Lift the skips, draw integers explicitly and give the numpy indexer the
same dropped-axis result, enable the vindex write with a duplicate-point
filter, and let any chunk that fits the array be sharded (33 of 500 now).
With these changes test_oindex fails against the code before this PR with
the mixed-integer shape mismatch, and passes with it.

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

* test: assert invalid value ranks are rejected on chunked and sharded arrays alike

Replace the sharded-only wrong-rank test in test_sharding.py and the GH2469
one-off in test_indexing.py with one parametrized error test: a coordinate
write with twice the elements, a mask write with a 2-D value, and an
orthogonal write with an extra axis each raise ValueError on chunked and
sharded arrays under both codec pipelines. The property under test is that
storage layout does not change which writes are rejected, which a
sharded-only test could not state. zarr_array_from_numpy_array grows a
shards argument for it.

Only the rejection is asserted; a write that fails inside the chunk merge
may already have touched other chunks on a chunked array.

Assisted-by: ClaudeCode:claude-fable-5-1
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

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Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>